In the late 1980s and early 1990s, one pharmaceutical company was named the world’s “most admired” company by Fortune magazine seven years in a row. During those years, the pharmaceutical industry was widely recognized for its integrity and productivity. What more noble activity is there than curing or preventing disease? Much of the progress in the pharmaceutical industry was based on foundational biological science performed by academicians and government scientists.

However, for the last ten years, there has been intense criticism of the research pharmaceutical industry over questionable practices (see table 1) (Angell 2004, 2008; Relman 2008; Steinbrook 2009). Although the industry argues that many of these practices are actually positive (e.g., direct-to-consumer advertising “educates” the public), the consensus of those outside the pharmaceutical industry is that these practices are, on balance, harmful. In fact, although there are many well-documented flagrant examples in newspapers, magazines, and books, it is extremely difficult to obtain quantitative data on the frequency of these practices. However, in general, I agree with these criticisms (see table 1). The industry has also been criticized for the lack of research and development productivity considering the amount of money spent.

But to obtain a balanced view of pharmaceutical progress (or lack thereof), we need to step back, define a few terms and concepts, and make explicit certain assumptions. Only then can we evaluate the “good” done by new pharmaceutical products over the last thirty years versus the abuses in table 1. I will refer to drugs by their chemical names and use generic (off patent) examples as much as possible, since generics are generally much cheaper and in many cases as good as or better than brand name drugs in their class.

Obviously, pharmaceutical agents, including vaccines, should prolong life or significantly decrease clinical disease and its attendant pain and suffering with minimal or no side effects. In other words, the risk/benefit ratio should favor the patient and the costs should be reasonable.

Generally, in thinking about prevention and treatment, we divide prevention of disease into two categories: primary and secondary. Primary prevention is treatment in high-risk persons to prevent disease; secondary prevention is treatment to prevent further disease. Examples of primary prevention are vaccines to prevent disease or the use of a now generic statin (e.g., simva­statin) to prevent heart attacks and strokes in high-risk persons. With simvastatin, secondary prevention would prevent deaths and further heart attacks and/or strokes in patients with previous episodes (see below). Treatment is the use of drugs to ameliorate disease—sometimes with a curative intent.

To prove the value of preventatives (including vaccines) and treatments, the European Medicines Agency and the U.S. FDA have rigorous “gold standard” criteria discussed in the Method­ological and Statistical section of a recent article in the Skeptical Inquirer and other publications (Spector 2009; Spector and Vesell 2006a). Generally, this involves doing two large (i.e., thousands of patients) randomized blinded trials of the drug versus a placebo (or comparator agent) that both show statistically significant results (Spector and Vesell 2006a). These studies are carried out after dose-finding studies in which the correct dose is determined. Ideally, the endpoint of such trials should be the number of deaths or events (e.g., heart attacks), but sometimes surrogate markers are accepted (e.g., lowering blood pressure or cholesterol) (Spector and Vesell 2006a).

Implicit in these standards is the definition of an ideal drug or vaccine (see table 2) (Spector 2002). Note that ideal drugs and vaccines must also stand the “test of time.” Table 3 shows examples of ideal (or near ideal) drugs discovered, developed, and marketed in the last thirty years. There is now nearly universal agreement (because of the large number of controlled trials) that moderate doses of statins not only lower blood cholesterol but substantially decrease death (secondary prevention) by about 30 percent and heart attacks and strokes by 30 to 50 percent (Scandinavian Simvastatin Survival Study [4S] 1994). To show the quantitative importance of these results, based on data from the 4S trial in patients with stable heart disease or angina, 12 percent died on placebo and only 8 percent died on simvastatin in five years. This 4 percentage point differential (assuming there are ten million U.S. patients with stable coronary heart disease [CHD], a conservative estimate, who took simvastatin) amounts to four hundred thousand fewer deaths due to the drug in five years. Aspirin, beta-blockers, and angiotensin converting enzyme (ACE) inhibitors or sartans (see below) each save about 5 to 15 percent of lives in such patients. When statins are appropriately combined with these drugs, there is probably about a 50 percent improvement in survival, or six hundred thousand lives (per ten million) saved in CHD patients over five years (Baker et al. 2009). In primary prevention, statins decrease heart attacks, strokes, and procedures by 20 to 50 percent depending on the population (Baigent et al. 2005; Brugts et al. 2009). The side effects and cost of moderate doses of statins (now generic) are generally not issues. Notwithstanding these impressive results, there is obviously more work to be done.

The now generic ACE inhibitors and the newer sartans effectively lower blood pressure with minimal side effects and decrease strokes, heart failure, and kidney damage (see table 3) (Spector and Vesell 2006b).

Proton pump inhibitors (PPI), which block stomach acid secretion, have had a huge impact on common stomach and esophageal disorders—disorders, in large part, due to stomach acid—including dyspepsia, ulcer, gastritis, and esophagitis due to acid reflux. Moreover, stomach operations for the complications of stomach and duodenal ulceration (perforation, obstruction, bleeding, and intractable pain) since the marketing of histamine blockers and especially PPI have decreased dramatically. Millions of Americans with these problems have been cured or have had their symptoms controlled with a safe daily pill or two—and no surgery (Spector and Vesell 2006c). Helicobacter pylori, a bacterium that often plays a contributory role in stomach ulceration, is also eliminable with antibiotics (Spector and Vesell 2006c). (This latter work led to a Nobel Prize.)

Certain newer antibacterial agents, including penems and ceftriaxone, save lives with minimal side effects. The penems have a very broad spectrum and kill bacteria (i.e., they are bacteriocidal). Similarly, ceftriaxone is generally bacteriocidal and needs to be given parenterally (i.e., by injection) only once daily—thus allowing for outpatient therapy of serious bacterial infections.

The vaccines listed in table 3, marketed over the last thirty years, are remarkably effective and safe. These vaccines are over 95 percent effective in preventing clinically significant disease (Offit 2008). One exception is the varicella vaccine, after which mild cases can still occur.

Finally, table 3 contains three examples of cancer chemo-preventatives. Hepatitis B, which in the past has infected hundreds of millions of people, can be eliminated by vaccination, with an attendant decline in liver cancer—a consequence of chronic hepatitis B infection (Offit 2008). Similarly, the current papilloma virus vaccines prevent infection with virus types 16 and 18, reducing cervical cancer in women by about 70 percent. And 5-alpha-reductase inhibitors can decrease cancer of the prostate by about 20 percent. These three examples are one of the few bright spots in the war on cancer (see below).

Examples of moderately useful drugs are shown in table 4. Before the mid-1990s, there were no useful, nonhormonal drugs for the treatment and prevention of osteoporosis and fractures—a huge clinical problem. Now, bisphosphonates can prevent approximately 50 percent of vertebral fractures and 25 percent of hip fractures—a good but obviously imperfect result. Moreover, they can be taken orally once weekly, once monthly, or intravenously once yearly (Spector and Vesell 2006b).

The new calcium channel blockers are effective agents in the treatment of high blood pressure but cause edema (swelling) in 5 to 15 percent of users. They do, however, prevent strokes, renal damage, and heart failure more than placebo.

The H-2 histamine blockers inhibit histamine-stimulated acid production by the stomach but are not as effective as the PPI discussed in table 2. However, for the treatment of milder acid-induced stomach disorders (heartburn, dyspepsia, esophageal reflux), they are useful, safe, and very inexpensive.

The tumor necrosis factor alpha (TNF a) blockers are the first of the biotechnology drugs useful in crippling rheumatoid arthritis (RA) and psoriasis. However, they have substantial and serious side effects, placing some patients at risk of severe infectious diseases. Their ability to slow or stop the relentless progression of RA puts the risk/benefit ratio in most patients’ favor, but these patented drugs are also expensive.

Finally, the SSRIs (see table 4) have a complex developmental history in the treatment of depression and generalized anxiety, but what is now clear is that the SSRIs are barely better than placebo in patients with mild depression (Mayer 2008). In severe depression, however, they are unequivocally useful with acceptable side effects. Severe depression is a devastating disease that ruins lives and can lead to suicide and other dire consequences. The SSRIs are helpful in these patients but by no means generally curative (Mayer 2008).

The three vaccines listed in table 4 (which were developed in the last twenty years) prevent shingles, childhood pneumococcal infections, and influenza, respectively, in 25 to 75 percent of vaccinated subjects. Specifically, the shingles vaccine prevents 75 percent of severe cases of shingles and 50 percent of total cases. Severe cases of shingles can affect the eye, causing terrible pain and damage to the cornea with loss of vision; more commonly, shingles can cause a severe chronic pain syndrome in the affected area that, on occasion, can drive people to suicide. The problem with the influenza vaccine is that it is formulated and manufactured before the flu season and thus sometimes the current formulation is ineffective against the current strain (compare the unexpected outbreak of “swine” flu in 2009).

Shown in table 5 are examples of FDA-approved drugs that are barely better than placebo on the average (P<.05 in two studies, although there were also negative studies) (Spector and Vesell 2002; 2006a). For example, loratadine is about 12 percent better than placebo (on the average) in relieving symptoms of allergic rhinitis; montelukast is even worse (about 6 percent), according to the company’s own label. To me, it seems outrageous to pay around $3 for a tablet of montelukast for a 6 percent chance of effect, when safe generic drugs yield a 20 to 60 percent response and are cheaper. In my view, the wide use of montelukast for allergic rhinitis is an example of the power of noncomparative direct-to-consumer advertising (see table 1). Similarly, 4 mg of tolteradine daily (for overactive bladder) gives (net of placebo) a less than 10 percent decrease in trips to the bathroom (micturations) and a less than 20 percent decrease in “accidents” (incontinence). Tol­teradine also has side effects (e.g., dry mouth, urinary retention) and contraindications to its use. Finally, tacrine is liver-toxic, and it has never been established that tacrine has clinical utility.

I would place many of the newer cancer drugs, especially the biotechnology agents, in table 5. In fact, in a recent thoughtful analysis of cancer therapy, Gina Kolata (2009) of The New York Times pointed out the minimal progress (with a few notable exceptions, like the treatment of chronic myelogenous leukemia with Gleevac) in the “war against cancer.” She points out that we are only 5 percent better off today than we were in 1950, notwithstanding billions of dollars spent on cancer research and treatments. Alas, there has been little progress against the major cancers (e.g., lung, stomach, pancreas, brain, breast, renal, etc.) when surgeons cannot totally remove it. (For more, see Kolata’s piece and my article “The War on Cancer: A Progress Report for Skeptics,” SI, January/February 2010.) This is in stark contrast to the tremendous progress against heart disease and stroke.

Discussion

As a society, where should we go from here with the problems outlined in table 1? Notwithstanding the hundreds of articles and books (see, for example, Angell’s work in 2004 and 2008), as noted above, it is difficult to assess quantitatively the magnitude of the questionable practices in table 1. In fact, though we have all seen fancy mainstream drug advertising that contains no quantitative data (e.g., how much improvement there is on the average) or important comparative data (e.g., in allergic rhinitis ads), there are some advertisements that are accurate and informative. But clearly misleading direct-to-consumer ads should be stopped.

There is also no doubt that some companies have flagrantly covered up negative data. In some cases, after being “caught” the companies paid hundreds of millions of dollars in fines or, in one recent case, settled with harmed patients for $5 billion (Singer 2009).

Almost everyone outside the industry feels an excessive amount of money is spent on misleading advertising—especially for drugs like those in table 5 that would not “sell themselves.” Also, the use of ghost writers and excessive payments to thought leaders, florid conflicts of interest, and payments to practicing physicians to encourage specific drug use clearly occur (see table 1). These practices should be outlawed (Stein­brook 2009).

Finally, scientifically worthless seeding studies (i.e., studies that do not test a hypothesis but are meant to familiarize physicians with the drug with the intent of increasing sales) may be on the wane, as is publishing only positive data and encouraging biased talks and literature. The press, academicians, journals, and public have wisely cracked down and lampooned such practices endlessly.

However, I submit that incredible good has been done by the drugs and vaccines in tables 3 and 4 (and many others not mentioned because of space limitations, like erythropoetin for certain types of anemia). As I discussed above, generic statins, ACE inhibitors, beta-blockers, and aspirin used in patients with coronary heart disease (CHD) save hundreds of thousands of lives yearly worldwide. Moreover, these drugs, when used optimally in patients with stable CHD, are as effective as invasive surgical procedures (e.g., coronary artery stenting) in most patients (Boden et al. 2007). Great progress against fatal heart disease (64 percent decline since 1950) and fatal stroke (74 percent decline since 1950) has been made in the face of increasing obesity and diabetes mellitus—two problems that exacerbate CHD and stroke (Kolata 2009). The drugs in table 3 and old drugs like beta-blockers and aspirin have made these tremendous advances possible.

The vaccines in table 3 basically eliminate the diseases (primary prevention) at which they are aimed. The harm done by hepatitis B alone—in the hundreds of millions—is now in principle eliminable with universal vaccination (Offit 2008). Hepatitis B is often a dreadful clinical problem and, as noted above, can lead to liver cancer (Offit 2008).

However, the failed war on cancer (Kolata 2009) and the lack of progress against Alzheimer’s and Parkinson’s diseases and many other chronic disabling diseases, unlike the tremendous progress made against heart disease and stroke, are very discouraging.

I would note that the drugs and vaccines in table 4, al­though not ideal, are also very useful; the risk/benefit ratio is clearly in the patient’s favor.

We should encourage the discovery and development of drugs and vaccines like those in table 3—especially against unsolved medical problems like cancer and Alzheimer’s and Parkinson’s diseases. Equally important, we should bridle or stop the abuses in table 1 and demand honest advertising of the drugs in table 5 (i.e., quantitative differences from placebo and comparative efficacy results). The abuses in table 1 could be eliminated by the combined and concerted efforts of the FDA, Securities and Exchange Commission, universities, journals, and medical societies. The FDA should also allow easier access to unpublished negative studies, as has been done with antidepressants (SSRI), allowing their “true efficacy” to be calculated (Mayer 2008).

Finally, the old saw that efficacy data must be clinically im­por­tant and not just statistically significant (Spector and Vesell 2006a; Spector 2009) must never be forgotten. Unbiased and objective experts, beholden to the public good, should discourage the pharmaceutical industry from marketing drugs that are statistically better than placebo but have no clinically meaningful efficacy. The FDA does not do this; they approve drugs but do not generally make comparative judgments.

In summary, over the past thirty years the pharmaceutical industry has made tremendous progress leading to greatly improved health and longer life spans with a substantial and correct focus on primary and secondary prevention, not just treatment, notwithstanding its failures (e.g., against cancer, Alzheimer’s and Parkinson’s diseases). In my view the future is bright with the steady march of new scientific progress. The problems in table 1 need work, but the solutions are obvious and should be relatively easily corrected. l

Acknowledgments

I wish to thank Michiko Spector for her help in the preparation of this manuscript.

References

Angell, M. 2004. The Truth about the Drug Companies: How They Deceive Us and What to Do About It. New York: Random House.

———. 2008. Industry-sponsored clinical research: A broken system. Journal of the American Medical Association 300: 1069–1071.

Baigent, C., et al. 2005. Cholesterol Treatment Trailists’ (CTT) collaboration. The Lancet 366: 1267–1278.

Baker, W.L., et al. 2009. Systematic review: Comparative effectiveness of angiotensin-converting enzyme inhibitors or angiotensin II–receptor blockers for ischemic heart disease. Annals of Internal Medicine 151: 861–871.

Brugts, J.J., et al. 2009. The benefits of statins in people without established cardiovascular disease but with cardiovascular risk factors: Meta-analysis of randomized controlled trials. British Medical Journal 338(301): b2376, June 30.

Boden, W.E., et al. 2007. Optimal medical therapy with or without PCI for stable coronary disease. New England Journal of Medicine 356: 1503–1516.

Kolata, G. 2009. In long drive to cure cancer, advances have been elusive. The New York Times. April 24, p.A1, A17.

Mayor, S. 2008. Study shows difference between antidepressants and placebo is significant only in severe depression. British Medical Journal 336: 466.

Offit, P.A. 2008. Vaccinated: One Man’s Quest to Defeat the World’s Deadliest Diseases. New York: Collins.

Relman, A.S. 2008. Industry support of medical education. Journal of the American Medical Association 300: 1071–1073.

Scandinavian Simvastatin Survival Study Group. 1994. Randomized trial of cholesterol lowering in 4444 patients with coronary heart disease (4S). The Lancet 344: 1383–1389.

Singer, N. 2009. Trial puts spotlight on Merck. The New York Times, May 14 p.B1.

Spector, R. 2002. Progress in the search for ideal drugs. Pharmacology 64: 1–7.

———. 2009. Science and pseudoscience in adult nutrition and practice. Skeptical Inquirer 33(3) (May/June): 35–41.

———. 2010. The war on cancer: A progress report for skeptics. Skeptical Inquirer 34(1) (January/February): 25–31.

Spector, R., and E.S. Vesell. 2002. A rational approach to the selection of drugs for clinical practice. Pharmacology 65: 57–61.

———. 2006a. Pharmacology and statistics: Recommendations to strengthen a productive partnership. Pharmacology 78: 113–122.

———. 2006b. The heart of drug discovery and development: Rational target selection. Phamacology 77: 85–92.

———. 2006c. The power of pharmacological sciences. Pharmacology 76: 148–156.

Steinbrook, R. 2009. Controlling conflicts of interest: Proposals from the Institute of Medicine. New England Journal of Medicine 360: 2160–2165.

In 1971, President Nixon and Congress declared war on cancer. Since then, the federal government has spent well over $105 billion on the effort (Kolata 2009b). What have we gained from that huge investment? David Nathan, a well-known professor and administrator, maintains in his book The Cancer Treatment Revolution (2007) that we have made substantial progress. However, he greatly overestimates the potential of the newer so-called “smart drugs.” Re­searchers Psyrri and De Vita (2008) also claim important progress. However, they cherry-pick the cancers with which there has been some progress and do not discuss the failures. Moreover, they only discuss the last decade rather than a more balanced view of 1950 or 1975 to the present.

On the other hand, Gina Kolata pointed out in The New York Times that the cancer death rate, adjusted for the size and age of the population, has decreased by only 5 percent since 1950 (Kolata 2009a). She argues that there has been very little overall progress in the war on cancer.

In this article, I will focus on adult cancer, since child cancer makes up less than 1 percent of all cancer diagnosed. I will then place the facts in proper perspective after an overview of the epidemiology, diagnosis, and treatment (especially with smart drugs) of adult cancer in the United States.

The Cancer Facts

Figure 1 shows the ten biggest killers in the United States in 2006. Cancer (23 percent) has almost caught up with heart disease. Figure 2 shows the death rates from cancer in men and women (adjusted for the size and age of the population) since 1975; the cancer death rates have declined in men but not in women. The decline in men is largely due to fewer lung cancer deaths in men due to less smoking (see figure 3). However, there were about 200,000 more deaths from cancer in 2006 than 1975 because of the substantial increase in the U.S. population.

These summary statistics show that the war on cancer has not gone well. This is in marked contrast to death rates from stroke and cardiovascular disease (adjusted for the age and size of the population), which have fallen by 74 percent and 64 percent, respectively, from 1950 through 2006; and by 60 percent and 52 percent, respectively, from 1975 through 2006 (Kolata 2009a). These excellent results against stroke and heart disease are mainly due to improvements in drug therapy, especially the control of high blood pressure to prevent stroke and the use of statins, aspirin, beta blockers, calcium channel blockers, and ACE inhibitors (now all generic) to prevent and treat heart disease. Cancer therapy is clearly decades behind. However, these data conceal a great deal of useful information and do not provide guidance on how to make progress against cancer.

Methodological Issues

To understand the issues, we must describe a few statistical traps and define our terms (see table 1). For example, there are several types of detection bias. First, if one discovers a malignant tumor very early and starts therapy immediately, even if the therapy is worthless, it will appear that the patient lives longer than a second patient (with an identical tumor) treated with another worthless drug if the cancer in the second patient was detected later. Second, detection bias can also occur with small tumors, especially of the breast and prostate, that would not harm the patient if left untreated but can lead to unnecessary and sometimes mutilating therapy. Another type is publication bias, whereby positive studies (especially those funded by the pharmaceutical industry) tend to be published while negative studies do not.

What is cancer? Cancer is a large group of diseases characterized by the uncontrolled growth and spread of abnormal cells locally, regionally, and/or distantly (metastatically) (American Cancer Society 2009). A carcinoma (cancer) in situ is a small cancer that has not invaded the local tissue. Some cancers grow very slowly, and the patient may survive for ten years or more with minimal treatment. Other cancers (e.g., lung and pancreas) grow quickly and, even today, kill more than half of the patients in less than one year (see table 2) (American Cancer Society 2009). The therapy for cancer is generally surgery, if possible, and/or chemotherapy and/or radiation therapy. Chemo­therapy aims to kill the cancer cells, but most chemotherapeutic drugs are nonspecific and also kill sensitive normal cells, especially in the intestine and bone marrow. Radiation therapy is also nonspecific. In chemotherapy and radiation therapy, a partial response is defined as shrinkage of the tumor in each dimension by 50 percent; a complete response means no detectable tumor, but this does not necessarily mean a “cure.” Many complete responses are only transitory. Median survival is the length of time in which one-half of the patients in a cohort die.

What Do We Know about Cancer?

The “causes” of cancer are shown in table 3 (American Cancer Society 2009), though there is still much we don’t know. For example, we do not know exactly how smoking causes cancer; in most cases, we do not know how “acquired” mutations cause cancer. In some cancers, there are more than five hundred identifiable genetic abnormalities—no one knows which one(s), if any, is “causative” (Downing 2009). The importance of epigenetic changes is currently speculative. It is quite possible that there is a completely unknown causal mechanism in many cancers.

The diagnosis of cancer today is relatively straightforward with imaging techniques (x-ray, CAT, MRI, PET) and biopsies that are subjected to routine histology, electron microscopy, and immunological techniques.

Cancer Therapy

To have a reasonable discussion of cancer therapy, we need to agree on the objectives of therapy (Fojo and Grady 2009), as shown in table 4. Everyone agrees that meaningful prolongation of life, preferably complete surgical removal of the tumor and cure, is a high priority. The treatment should also improve the quality of life. But, as is well known, many chemotherapeutic and radiation regimens cause mild to devastating—even fatal—side effects. Nathan (2007) compares conventional chemotherapy to “carpet-bombing,” an extreme but realistic metaphor. Finally, the results of a cost-benefit analysis must be reasonable (Fojo and Grady 2009). (In some cases, justifiably and importantly, chemotherapy and/or radiation and/or other drugs are used as palliative measures exclusively to counter symptoms from the disease [e.g., pleural effusions in the chest cavity or bone pain] or from the treatments [e.g., vomiting, mucositis, low white blood counts, heart failure, nerve damage, diarrhea, and/or inflammation of the bladder]). In the final analysis, what counts are the criteria in table 4. Partial or even complete remissions, unless they prolong life and/or improve the overall quality of life at a reasonable cost, are scientifically interesting but of little use to the patient.

Currently there are a few metastatic cancers that can sometimes be cured with chemotherapy and/or radiation therapy, but unfortunately these cures make up a very small percentage of the whole cancer problem. These cancers include testicular cancer, choriocarcinoma, Hodgkin’s and non-Hodgkin’s lymphoma, leukemia, and rare cases of breast and ovarian cancer. A few cancers can be made into chronic diseases that require daily treatment, e.g., chronic myelogenous leukemia.

Returning to table 2, lung cancer, the most common cancer, is a devastating disease; if the surgeon cannot totally remove it, the diagnosis is grim. In fact, about 60 percent of lung cancer patients are dead within one year of diagnosis with the best available therapy, and only 15 percent survive five years.

There has been some progress in the death rate from colo­rectal cancer (figures 4 and 5), especially in women. This is mainly due to earlier diagnosis and surgical therapy.

Cancer of the breast is often a slow cancer and has a five- to ten-year median survival rate with just surgical therapy. As can be seen in figure 5, there has been a modest decline in death rates from breast cancer since 1975. It is worth noting that currently, if the breast cancer is metastatic, five-year survival is only 27 percent (American Cancer Society 2009). However, breast cancer presents a serious dilemma. Early detection of invasive breast cancer by screening is good; however, about 62,000 cases of ductal carcinoma in situ (DCIS) are also discovered every year (American Cancer Society 2009). In greater than 50 percent of these women, especially older women, these lesions will not progress and do not need treatment. However, it is difficult to predict who will not need therapy, so the American Cancer Society (2009) recommends all patients with DCIS undergo therapy—generally breast surgery. Thus, more than thirty thousand patents annually are unnecessarily treated (Evans et al. 2009). We need to figure out which DCIS are harmless in order to avoid unnecessary treatment. On balance, I feel that breast cancer screening has a small but positive net benefit (Esserman et al. 2009).

Pancreatic cancer is devastating (see table 2 and figures 4 and 5), and little progress has been made against it since 1975. Pancreatic cancer is very challenging because the tumors are surrounded by dense fibrous connective tissue with few blood vessels (Olson and Hanahan 2009). Because of this, it is difficult to deliver drugs to pancreatic tumors. Moreover, this explains in part why chemotherapy is so ineffective for pancreatic cancer (see table 2). Better animal models are needed.

Prostate cancer mortality has declined slightly since 1975 with an unexplained increase in the mid-1990s (see figure 4). But prostate cancer therapy also presents a serious quandary. At autopsy, approximately 30 percent (or more) of men have cancer foci in their prostate glands, yet only 1 to 2 percent of men die of prostate cancer. Thus less than 10 percent of prostate cancer patients require treatment. This presents a serious dilemma: whom should the physician treat? Moreover, recently, two large studies of prostate cancer screening with prostate specific antigen (PSA) have seriously questioned the utility of screening. In one study, the investigators had to screen over a thousand men before they saved one life. This led t o about fifty “false positive” patients who often underwent surgery and/or radiation therapy unnecessarily (Schröder et al. 2009). The second study, conducted in the United States, was negative (Andriole et al. 2009), i.e., no lives were saved due to the screening, but many of the screening-positive patients with prostate cancer were treated. Welch and Albertson (2009) and Brawley (2009) estimate that more than a million men in the U.S. have been unnecessarily treated for prostate cancer between 1986 and 2005, due to over-diagnostic PSA screening tests. In the end, screening for prostate cancer will not be useful until methods are developed to determine which prostate cancers detected by screening will harm the patient (Welch and Albertson 2009; Brawley 2009). Many men—especially elderly ones—with a histological diagnosis of prostate cancer elect “watchful waiting” with no therapy, a rational strategy (Esserman et al. 2009).

There are many other things we do not understand about cancer—even on a phenomenological level. For example, in the United States, the incidence and death rates from cancer of the stomach have fallen dramatically since 1930 (see figures 4 and 5). The reason for this is unknown but may be due to changes in food preservation; it is not due to treatment.

Smart Drugs

David Nathan (2007) extols the virtues and potential of the new “smart drugs.” Smart drugs are defined as drugs that focus on a particular vulnerability of the cancer; they are not generalized but rather specific toxins. But the Journal of the American Medical Association (Health Agencies Update 2009) reports that 90 percent of the drugs or biologics approved by the FDA in the past four years for cancer (many of them smart drugs) cost more than $20,000 for twelve weeks of therapy, and many offer a survival benefit of only two months or less (Fojo and Grady 2009). Let us take bevacizumab (Avastin), the ninth largest selling drug in America ($4.8 billion in 2008), costing about $8,000 per month per patient (Keim 2008). Bevacizumab, a putative smart drug, is an intravenous man-made antibody that blocks the action of vascular endothelial growth factor (VEFG). It sometimes works because tumors (and normal tissues) release VEFG to facilitate small blood vessel in-growth into the tumor. These small blood vessels “nourish” the tumor (or normal tissue). The idea is to “starve” the growing tumor with once or twice monthly intravenous injections of bevacizumab.

The FDA has approved bevacizumab for the cancers listed in table 5 (Physicians Desk Reference [PDR] 2009; Health Agencies Update 2009). Since the median survival of colorectal cancer is eighteen months, bevacizumab therapy would cost about $144,000 (in such a patient) for four months prolongation of survival (Keim 2008). In the other cancers in table 4, there is no prolongation of survival. Moreover, bevacizumab can have terrible side effects, including gastrointestinal perforations, serious bleeding, severe hypertension, clot formation, and delayed wound healing (PDR 2009). By the criteria in table 4, bevacizumab is at best a marginal drug. It only slightly prolongs life, demonstrable only in colorectal cancer, has serious side effects, and is very expensive.

Bevacizumab is frequently cited as an example of the so-called newer smart drugs. But by interfering with small blood vessel growth throughout the body, it is a nonspecific toxin—and hence has serious side effects. It is not so different from the older non-specific chemotherapy.

The use of bevacizumab and similar drugs raises another issue. According to Gina Kolata, 60 to 80 percent of oncologists’ revenue comes from infusion of anti-cancer drugs in their offices. Many believe that such economic incentives are the reason for the substantial overuse of expensive chemotherapeutic drugs (Kolata 2009c). However, it is very difficult to document the extent of the overuse of cancer chemotherapy. Does it make sense to employ such expensive drugs that do not prolong life (see table 5) and have such serious side effects (Fojo and Grady 2009)? Moreover, although VEGF and bevacizumab are interesting science, there has been gross exaggeration of bevacizumab’s clinical utility in the press (see tables 4 and 5).

So why does the U.S. Food and Drug Administration (FDA) approve bevacizumab (and other drugs) that do not improve longevity and/or the quality of life (see table 5)? The answer is that bevacizumab coupled with other drugs can cause partial remissions, “stabilization” of the cancer, or “lack of progression” for several months. However, this often does not lead to prolongation of life in most of the cancers in table 5. Moreover, many patients pay a heavy price in terms of side effects and cost. It is also worth noting that several European national regulatory authorities do not accept the utility of some of these smart drugs and do not license them for sale in their countries. In agreement with the Europeans, scientists at the U.S. National Cancer Institute are urging the oncology community, regulators, and the public to set limits on the use and pricing of such marginal drugs (Fojo and Grady 2009). They view the current situation as unsustainable.

Why Has the War on Cancer Failed?

As documented above, unlike the successes against heart disease and stroke, the war on cancer, after almost forty years, must be deemed a failure with a few notable exceptions (Watson 2009). Why? Is it because cancer is an incredibly tough problem, or are there other explanations? In table 6, I have listed six reasons for the failure, although there is little doubt that effective, safe therapy of the various cancers is a difficult problem.

Where Should We Go from Here?

In my view the principal problem is that we just do not understand the causes of most cancers. We don’t even know if the problem is genetic or epigenetic or something totally unknown. In theory, problems 2 through 6 in table 6 are all correctable with political and scientific will and more knowledge. Even though we know cancer of the lung is caused by cigarette smoking, we do not know the mechanism, and (except for surgery) we do not know how to meaningfully intervene (see table 2). The pharmaceutical industry cannot make real progress until we understand the mechanisms and molecular causes of cancer so that industrial, academic, and governmental scientists have rational targets for intervention. We will make no progress if there are five hundred or more genetic abnormalities in a single cancer cell. Where would one begin?

What Should We Do Now?

We can still do a lot even today (see table 7). Smoking and hormone replacement therapy are a cause of lung and breast cancer, respectively, and should be stopped or minimized. For hepatitis B (which causes over 50 percent of liver cancer) (Chang et al. 2009) and papilloma virus (which causes almost all cervical cancer and some anal and mouth cancers), we can vaccinate with vaccines that are essentially 100 percent effective. Helicobacter (the probable cause of some stomach cancer) can be easily eliminated with antibiotics. Prophylactic finasteride and tamoxifen (both generic) can decrease prostate and breast cancer, respectively (in high risk patients). We must also decrease alcohol intake (liver and esophageal cancer) and obesity. Obesity is associated with increased cancer risk but the mechanism, if causal, is obscure (Dobson 2009).

We can screen for cervical, colorectal, and breast cancer, although the value of breast cancer screening is not clear (due to overdiagnosis), as I discussed above (Singer 2009). How­ever, in my view, the benefit of breast cancer screening slightly outweighs the harm. For example, if DCIS treatment could be rationalized and provided only to those who need it, breast cancer screening would then be unarguably useful. All attempts to screen for lung cancer, even in smokers, have so far been futile (Infante et al. 2009).

If all these recommendations were followed, we could cut cancer deaths in half. Moreover, with better mechanistic understanding of cancer, we could make truly “smart” drugs, as has been done in recent years for atherosclerosis (heart attacks), hypertension (strokes), gastrointestinal diseases (ulcers), and AIDS—with truly remarkable results. Let us hope cancer is next.

Acknowledgments

I wish to thank Michiko Spector for her help in preparation of this manuscript and Dr. June Spector for her critical reading of the manuscript.

Tables / Figures

References

• American Cancer Society. 2009. Cancer Facts and Figures 2009. p.1–38.
• Andriole, G.L., R.L. Grubb III, S.S. Buys, et al. 2009. Mortality results from a randomized prostate-cancer screening trial. New England Journal of Medicine 360: 1310–1319.
• Brawley, O.W. 2009. Prostate cancer screening: Is this a teachable moment? Journal of the National Cancer Institute 101: 1295–1297.
• Chang, M-H, S-L You, and C-J Chen, et al. 2009. Decreased incidence of hepatocellular carcinoma in hepatitis B vaccinees: A 20-year follow-up study. Journal of the National Cancer Institute 101: 1348–1355.
• Dobson, R. 2009. Obesity is risk factor in 70,000 European cases of cancer a year. British Medical Journal 39: 316.
• Downing, J.R. 2009. Cancer genomes—continuing progress. New England Journal of Medicine 361: 1111–1112.
• Esserman, L., Y. Shieh, and I. Thompson. 2009. Rethinking screening for breast and prostate cancer. Journal of the American Medical Association 302: 1685–1692.
• Evans, A., E. Cornford, and J. James. 2009. Overdiagnosis of breast cancer. British Medical Journal 339: b3256.
• Fojo, T., and C. Grady. 2009. How much is life worth: Cetuximab, non-small cell lung cancer, and the $440 billion question. Journal of the National Cancer Institute 101: 1044–1048.
• Health Agencies Update. 2009. Journal of the American Medical Association 302: 838.
• Infante, M., S. Cavuto, F.R. Lutman, et al. 2009. A randomized study of lung cancer screening with spiral computed tomography. American Journal of Respiratory Critical Care Medicene 180: 445–453.
• Keim, B. 2008. Wired.com, February 28.
• Kolata, G. 2009a. In long drive to cure cancer, advances have been elusive. The New York Times, April 24.
• ———. 2009b. Playing it safe in cancer research. The New York Times, June 28.
• ———. 2009c. Lack of study volunteers is said to hobble fight against cancer. The New York Times, August 3.
• Nathan, D.G. 2007. The Cancer Treatment Revolution. Hoboken, NJ: John Wiley and Sons, Inc.
• Olson, P., and D. Hanahan. 2009. Breaching the cancer fortress. Science 324: 1400–1401.
• Physicians Desk Reference. 2009. Montvale, NJ: Thomson Reuters.
• Psyrri, A., and V.T. DeVita. 2008. The impact of research on the cancer problem: Looking back, moving forward. In: Everyone’s Guide to Cancer Therapy (5th ed.), 349–359. Kansas City: Andrews McMeel Publishing.
• Schröder, F.H., J. Hugosson, M.J. Roobol, et al. 2009. Screening and prostate-cancer mortality in a randomized European study. New England Journal of Medicine 360: 1320–1328.
• Singer, N. 2009. In push for cancer screening, limited benefits. The New York Times, July 17.
• Watson, J. 2009. To fight cancer, know the enemy. The New York Times, August 6.
• Welch, H.G., and P.C. Albertson. 2009. Prostate cancer diagnosis and treatment after introduction of prostate-specific antigen screening: 1986–2005. Journal of the National Cancer Institute 101: 1325–1329.

In recent years, nutrition research and practice have lagged behind many other biological and medical fields.^1-5 In part, this lag is due to many pseudoscientific beliefs and practices mistakenly regarded as being based on scientific methods.^1-5 By nutrition I mean all the foods, fluids, and “natural” supplements humans ingest.^1,2 By pseudoscience, I mean the use of inappropriate methods that frequently yield wrong or misleading answers for the type of question asked. In nutrition research, such methods also often misuse statistical evaluations.⁴ My purpose here is to definitively (wherever possible) or tentatively (where the data are incomplete or nonexistent) answer a series of key questions about adult human nutrition using relevant rigorous scientific principles and methods. The data clearly show that much current advice about dietary pyramids, food supplements, megavitamins, and weight loss regimens is frequently unproven, erroneous, or even harmful and is often based on pseudoscience or derivative incorrect professorial opinion.^1-7

But before coming to the answers, we should frame the general questions precisely:

1. What do we know about adult human nutrition that meets the standards for truth?
2. Is there an optimum body weight? Is the ancient wisdom of Aristotle correct? He preached a sound mind in a sound body and, most importantly, moderation in all things, including diet. Or are current (immoderate) claims that large amounts of certain nutrients (e.g., vitamins, lycopene, fruits, and vegetables) and avoidance of others (e.g., saturated fats like butter, rapidly absorbed carbohydrates like rice and potatoes) the “way” to prevent bodily harm and promote health?^{1,2,6, 7}
3. Why are there so many confusing or contradictory data and opinions in the literature, news media, and books on the following points?^1-5
• Are food supplements such as megavitamins—defined as greater than five times the recommended daily allowance (RDA)—helpful? Specifically, are megavitamins E, C, and carotene healthful or harmful? That is, will they prevent disease and aging alone or in combination? Is there even one supplemental nutrient (nutraceutical) proven to prevent disease and possibly prolong life?
• Are certain common foods (in moderation) harmful? For example, are dietary saturated fats really harmful? Or are such fats useful fuel burned in the body to harmless carbon dioxide and water to provide energy as described in the biochemistry textbooks? Are processed rice and potatoes really bad for you? Do rice and potatoes really strain insulin production by the pancreas and lead to diabetes as alleged?⁶ Or are rice and potatoes a reasonable source of calories ingested by billions without harm? In other words, are there some nutrients that can cause disease and others that can prevent disease and illness?^1,2,6 Are there “fountain of youth” nutritional approaches or do the body’s homeostatic mechanisms counteract “over-consumption” or “under-consumption” of most nutrients? Obviously, everything can be harmful in excess, even salt and water.
• Are there comparative studies that show that certain classes of foods are better or worse than others for adult human health? Are diets high in saturated fats worse than diets high in rapidly absorbed carbohydrates or animal proteins?
• Which weight-loss diets, if any, work?
4. Why are there so many erroneous or uninterpretable nutritional experiments (pseudoscience) in the literature? Why do so many scientifically contradicted claims persist in the literature?^3-5,7 Why are certain long-term epidemiology/observation studies (EOS) continued in spite of the persistent publication of pseudoscience from these studies?^1-5,7

To answer these four general questions, we need to understand the methods required to prove hypotheses conclusively in human nutrition and human health. We must apprehend the assumptions, methods to establish causality, clinical trial design, hierarchies of evidence, and statistical concepts so we can evaluate nutritional studies correctly,^3-5,8 i.e., to separate pseudoscience from science, falsehood from truth. Also, we need to understand the methods involved in extrapolating data from nutritional studies to inferences about populations. For example, data in children or young adults may not be transferable to the elderly (e.g., milk tolerance and vitamin B-12 absorption are different in children than in the elderly).

Finally, we must understand what the U.S. Food and Drug Administration (FDA) and other regulators require for assessing and approving nutritional claims and drugs.^3-5,8 Within the limits of its jurisdiction (see below), the FDA generally evaluates claims of the type “X causes Y” based on rigorous scientific standards before accepting a causal claim.^1-4,8 This is in contrast to many journal editors, academic and governmental nutritional committees (e.g., the Department of Agriculture), and the media, which often have weak scientific standards.^1,2 I will briefly review the FDA standards below.

With a rigorous scientific approach, we can then distinguish “true” nutritional claims with some certainty—separate facts and reasonable inferences from false claims and unproven hypotheses where there is inadequate, incorrect, or misinterpreted data.

In an accompanying document entitled “Methodological and Statistical Issues in Adult Nutritional Research,” available on the Skeptical Inquirer Web site, I describe in some detail the relevant methodological and statistical issues. This analysis is critical to understanding the results of much nutritional research, and I recommend it to interested readers. For example, many EOS widely used to assess causality (e.g., that megavitamin E decreases cardiovascular risk) are methodologically unable to do so.^4,5,7 Yet they are frequently performed and published. I explain this strange phenomenon and other methodologically important issues in the “Methodological and Statistical Issues . . .” document.

What Do We Know?

In fact, we know a lot about adult human nutrition. As shown in Table 1, there are a number of nutrients and minerals humans must ingest for health and well being throughout life. For most adults, except as noted below, these nutrients and minerals are readily obtained from a balanced diet without the need for supplements.⁹ Lack of these will lead to poor health and even death. However, it is true that in four- to six-week experiments in obese subjects, only water, vitamins, and minerals, especially potassium chloride, were required. In fact, very obese patients can survive in excellent health for many months on only water, vitamins (in RDA doses), and potassium chloride.¹ Potassium is required to make up for its obligatory loss through the kidney. In these starving, obese people, calories are mainly obtained through fat mobilization with attendant weight loss. But over the long term, the nutrients and minerals in Table 1 must be ingested. As noted in Table 1, however, the need for calories (fuel) can mainly come from carbohydrate, fat, protein, or combinations of these three. The need for the essential substances in Table 1 is not controversial.^{1,6, 9}

Table 2 shows three important principles of biochemical and physiological nutrition. First, a healthy person (given RDA intake of the substances in Table 1) can proceed with a normal (see below), stable weight by eating predominantly fat or carbohydrates or protein or various combinations of these because of the body’s ability to interconvert and utilize carbohydrates, fats, and proteins (amino acids) as needed. In other words, fat, carbohydrate, or protein can serve as the principal source of calories.

Second, the body has a remarkable ability to maintain relatively constant blood levels (homeostasis) of many nutrients. Even more remarkable is the ability of the central nervous system, testicles, and ovaries to maintain nutrient homeostasis. For example, in two carefully studied cases, even huge fluctuations in (orally) ingested potassium or vitamin C barely changed the concentrations of these substances in cerebrospinal fluid (CSF) or the brain.¹⁰ We now understand the biochemical, molecular, and genetic bases for such remarkable homeostasis in the CSF and brain.^10,11 This has profound implications for attempting to prevent cognitive decline with certain nutrients as discussed below.

Finally, with aging, there are large changes in nutritional needs and metabolism. For example, there is approximately a 1 percent decrease per year in energy requirements after age thirty. As we age, there are also major changes in many functions in some individuals, for example, decreases in the enzyme lactase (in the gastrointestinal tract), which splits lactose to easily absorbed galactose and glucose. Also, in some elderly persons, the ability to absorb certain essential substances, such as vitamin B-12, declines. These changes must be understood when talking about diets in the young versus in the elderly.

Is There an Optimum Weight for Adult Humans?

The answer is probably yes.¹² There is a large amount of epidemiological, pathological, and clinical data that suggests a body mass index (BMI) (defined as weight in kilograms divided by the square of height in meters) of approximately 20-25 is optimal. A BMI of greater than 30 is termed obese. There is also a large body of controlled evidence showing that animals fed a low-calorie diet (that keeps them “thin”) live longer and are healthier than heavier animals fed an “ad libitum” diet. These human and animal data satisfy Hill’s criteria noted in the “Methodological and Statistical Issues” document.^2-4,12 However, in humans there has never been a randomized controlled trial of food intake to keep BMI at 20-25 versus greater than 30 with morbidity (disease) and mortality the end points.¹² But, for this article, I accept the notion that obese humans, on average, are less healthy and/or die sooner than people with a BMI of 20-25, all other things being equal, although it is formally possible that obese individuals are “doomed” for reasons independent of obesity.

Controversial Questions Answered

Are food supplements helpful? Are there particular nutrients that will prevent illness and disease and possibly prolong life?

The answer, notwithstanding thousands of positive EOS and, in some cases, small inadequate clinical trials, is there is no rigorous scientific evidence for the utility of dietary supplements, including megavitamins in normal-weight (nonpregnant) adults with a stable BMI of 20-25 eating a diet containing adequate amounts of the nutrients in Table 1. See Table 3 for representative examples of false claims based on erroneous EOS.^2-5,9,13-21 As you can see, the EOS have been frequently in error, yielding false-positive results. In general the clinical trials in Table 3 are examples of controlled, randomized studies done with very large numbers of people often versus placebo. (It is true, however, that in certain populations the RDA of a few vitamins might be slightly higher than in normal adults, e.g., vitamin D and possibly calcium for nursing home residents and others who do not go out in the sun, and vitamin B-12 for elderly people or for those on proton pump inhibitor drugs.) In fact, there is some evidence in controlled trials that megavitamins (e.g., E, C, and A) may actually increase mortality.¹⁴ Clear exceptions to the general lack of utility of megavitamins are extremely rare patients with genetic abnormalities, e.g., those with vitamin B6-responsive seizures.^10,11 Yet, notwithstanding the lack of evidence of benefit and potential harm, megavitamins and supplements are still recommended by some nutrition “experts.”9 It is worth noting that the nutraceutical (supplement) industry is a multibillion-dollar enterprise.^9,14 Dan Hurley summarizes the pseudoscience in this area in his excellent book Natural Causes.⁹

Focusing on the lack of scientific rationale for so many nutritional claims, many people ask why and how this sad state of affairs developed. For example, based on what has been known for over thirty years about brain and CSF vitamin homeostasis, how could so many EOS investigators hypothesize and then accept EOS (Table 3) that suggested that megavitamin E, C, and/or B could prevent cognitive decline in adults on diets adequate in the essential substances in Table 1?^10,11 Consumers and the public correctly ask: If you can’t increase brain levels of these vitamins by even large oral doses, how could they “work?” The Hill criterion for biological plausibility is clearly negative.^3-5 In fact, after spending hundreds of millions of dollars on scientific controlled trials, it is now clear that megavitamins do not work (Table 3).

What then is the reason for so many erroneous EOS? Is there a systematic bias? First, as discussed in the “Methodological and Statistical Issues” document, because they are not randomized, EOS are prone to bias and confounding. In many studies, one type of bias is healthy-person bias. In other words, healthier, more health-conscious people tend to take supplements. These people tend to have less disease regardless of the supplements. So, in such EOS it looks like the supplements help. If randomized studies had been conducted, this would not happen (Table 3).

Are certain foods, minerals, or supplements harmful?

Excess amounts of anything can be harmful. Especially noteworthy are vitamins A and D, which can be very toxic in high doses. Aristotle was generally correct—all things should be in “moderation.” He actually took this advice from an inscription on the temple of Apollo in Delphi, Greece. As I noted earlier, even widely used supplements such as vitamins E, C, and carotene in “standard mega-doses” (greater than five times the RDA) may indeed be harmful.¹⁴ The potential for harm for many other types of supplements has not been systematically studied, although there are convincing data that certain supplements may damage the liver, kidney, or heart or alter drug metabolism.⁹ For example, the amino acid tryptophan (used to induce sleep) and ephedrine-containing herbs (for asthma) were removed from the over-the-counter market because of severe toxicity, including deaths in some people.⁹ Unfortunately, the FDA does not generally evaluate supplement claims for safety and efficacy nor does not it regulate the content of most supplements.⁹ Hence, it is difficult to know the true content of these supplements. Moreover, when carefully measured, there are many examples of supplement labels not reflecting the true content, a deplorable situation.⁹

Are certain classes of foods better or worse than others?

In healthy people who ingest the essential nutrients in Table 1 and have a normal stable weight (BMI approximately 20-25), there is no convincing comparative outcome evidence (as I defined above) that common foodstuffs, e.g., saturated fats like butter, rapidly absorbed carbohydrates like white rice and potatoes, or animal proteins, are especially helpful or harmful. The notion that some diets (e.g., low-fat or low-carbohydrate) are better than others is not based on sound science but instead on flawed EOS.¹ The USDA food pyramid of the past (which prescribed what you should eat, how many portions, and disparaged certain nutritious foods like eggs and butter) was unscientific.^1,2,6 That food pyramid was based, in part, on EOS so flawed as to be almost ludicrous.^1,2 Specifically, there are no scientific outcome data (as defined above) that five daily servings of fruits or vegetables as per the original USDA food pyramid are better than two or that apples are better than pears (notwithstanding Ben Franklin) in normal-weight adults who consume the essential nutrients in Table 1. Let the proponents of such dietary advice prove the value of their advice with real outcome data from well-managed randomized controlled trials. Similarly, recent attempts to create new food pyramids are also flawed, for example, those that disparage rapidly absorbed carbohydrates (e.g., processed rice and potatoes) and recommend megavitamin E.⁶ Let the anti-potato and anti-rice proponents scientifically prove to billions of normal-weight adults or millions of older citizens with delayed gastric emptying (on diets adequate in the essential nutrients in Table 1) that potatoes or white rice per se are more harmful than whole wheat in scientific controlled outcome trials.

However, in obese individuals (BMI > 30), there is some evidence that not only do they eat too many calories but they may also be eating a diet (e.g., rapidly absorbed carbohydrates) that does not “satiate” them and leads to more rapid fat deposition.¹ This hypothesis remains to be proven.

Do weight-loss diets in obese people work?

None work well. On average, over the long term, obese humans do not lose much weight on voluntary low-calorie diets of any kind. (There are of course a few obese individuals who have “self discipline” and can lose weight and keep the weight off. Their “secret” is obscure.) There is, however, some evidence that low-carbohydrate diets “work” best at least for periods up to one year,22 but this has not been replicated in a two-year study.^22a Notwithstanding thousands of weight-loss articles and books, there has been very little progress in this area outside of surgical intervention.

Why is so much erroneous and pseudoscientific nutrition research and commentary published? Why do contradicted claims persist in the literature?

While the methodology to approach the truth in nutrition research has been known for decades, it is often either not followed or scientific data are resisted.^1-5,7,9 In attempts to understand why this happens, sociologists often employ a balanced analysis. A useful part of such an analysis is the question: who benefits from a particular event or behavior?^4,5,7 To begin to answer that question, it is necessary first to review past publication policies of leading medical journals.

In 1994, in a revealing editorial, the editors of the New England Journal of Medicine (who have published many erroneous EOS), in an Apologia in response to highly critical newspaper articles, attempted to justify publication of many conflicting (EOS) dietary studies on vitamins as chemo-preventive agents and the whole issue of dietary advice (e.g., butter vs. margarine).²³ Unfortunately, the editors did not claim that the goal of research should be the search for truth using the best available methods.^2-5,23 They did not acknowledge the hierarchy of evidence and the great value of well-conceived and executed experiments.^2-5,23 The editors seemed unaware that a few clear, convincing, well-conducted trials, when widely disseminated and followed, can change the practice of nutrition and medicine definitively, unlike hundreds of inconclusive studies, especially EOS.^2-5,7,23

Instead, the editors stated, “Thus, nearly every clinical research study would be seen as preliminary. . . . Doctors know that clinical research rarely advances in one giant leap; instead, it advances incrementally.”23 The editors did not blame themselves (and other editors) for publishing low-quality or uninterpretable papers. Instead, the editors blamed the media, which should “improve the way they interpret science.” Angell and Kassirer then stated that “the public at large needs to become much more sophisticated about clinical research, particularly epidemiology” because “what medical journals publish is not received wisdom but rather working papers.”23

Thus, they as journal editors placed the burden on the student, nutritionist, medical scientist, physician, public, and media to determine what is valid, important, and meaningful, sometimes with the help of editorials.²³ This is not a realistic expectation as can be seen in the chaotic state of nutritional research and practice.^1-5,7,9

Who benefits from such an editorial policy so profoundly dissonant with the scientific and regulatory principles described earlier?^3-5 Table 4 provides a tentative analysis of who benefits from poor-quality nutritional research and why.⁵ Table 5 reveals a similar tentative analysis of who is harmed and how.⁵

As I described earlier, unless proper studies are done (randomized, single variable, hypothesis-driven, with validated instruments and proper statistical analyses), the literature is doomed to potential, often-unknown bias and confounding.⁴ Although it is difficult and expensive to do long-term adequate nutritional studies, it is possible, and scientific studies have been done with megavitamins (e.g., E, C, folate, carotene), certain diets, and supplements9 with definitive results (Tables 1,3).

In view of the nutritional chaos I have described, it is a sad commentary on American regulatory authority that the FDA does not have the authority to regulate nutraceutical content and claims except when egregious safety concerns become apparent.⁹ Thus, the public is at the mercy of the media, journals, and company advertising (Tables 4,5), which is often misleading—from the subtle to the outrageous. This unfortunate state of affairs has recently been expertly reviewed.⁹

Finally, untrue claims that certain nutrients and nutraceuticals reduce cardiovascular risk and prevent cognitive decline or cancer (Table 3) steer patients away from safe, proven treatments that are often cheap and generic.^3-5 For example, generic aspirin, ACE inhibitors, and statins have been unequivocally proven to decrease cardiovascular risk and death in selected populations.^3-5

The issue of why there is such persistence of contradicted nutritional claims is discussed at length by J.P.A. Ioannidis’s group using megavitamin E as an example.⁷ They focus on “wish bias.”7 But the unwillingness of investigators who perform pseudoscientific studies to concede error and the role of commercial profit-driven interests cannot be underestimated.^3-5,9 It is worth noting that Walter Willet of the Harvard School of Public Health was still recommending megavitamin E in 2005 (at ten times the RDA),6 notwithstanding the overwhelming evidence that, if anything, megavitamin E is harmful.^9,14

In summary, the critics of nutritional research and practice suggest that much nutritional research and practice is, to paraphrase Thomas Hardy, science’s laughingstock, for two reasons: much of the research, especially EOS, is pseudoscientific for the reasons I have discussed and second, many practitioners and commercial interests do not readily acknowledge the truth.^1-5,7-9

Conclusions and Recommendations

The value of following the scientific principles noted above is well established.^{1-5; 7}-9

1. Readers of medical reports and journals should focus on studies that employ methods that test a hypothesis definitively. Readers should be skeptical of the results of EOS that test a contributory causal hypothesis and draw causal conclusions unless they satisfy the Hill criteria.^3-5 Such studies must be considered at best hypothesis-generating. Moreover, unless such studies have a clear “upfront” hypothesis and prespecified data analysis plan and are not the result of “data-dredging,” they merit even less credence.^3-5
2. Readers and viewers should encourage journals and the media to reform their publication and reporting standards. Journals should publish only scientifically sound studies and label most EOS as, at best, hypothesis-generating. Journals should have a section where authors who have published incorrect studies or nutritional advice can correct their views—analyze where they erred and discontinue defending erroneous and misleading publications.⁷ Journals should carefully edit opinions on nutritional and therapeutic advice, rather than leaving such advice mainly to authors. The criteria for recommendations should include “substantial evidence” for efficacy and safety (as per the FDA) as well as chemically defined ingredients to avoid disasters like the tryptophan recall described earlier.⁹
3. Readers should encourage journal editors, academicians, and funding agencies to support quality studies (e.g., randomized controlled studies) rather than those unlikely to answer questions definitively (e.g., EOS, case-control studies, or cohort studies). Special recognition should be accorded investigators who do difficult but definitive studies.

In the end, as Socrates pointed out, the big question is: How should one live one’s life? To decide, one needs good data! In terms of nutritional advice:

1. Demand scientific studies.
2. Follow the FDA criterion: only follow nutritional advice if proven to be safe and effective.
3. View the nutritional advice of “experts,” like those who prepared the agriculture department’s original food pyramid1 and the newer food pyramids,6 with a hypercritical eye. Their track record is poor.^1-5,7,9,10
4. Unless there is sound evidence, follow Aristotle’s principles:
• Aim for a sound mind in a sound, stable body with a BMI between 20-25.
• Practice moderation in nutritional matters.
• Observe Table 1—especially elderly people and those on certain drugs (e.g., diuretics that can deplete the body of essential substances) or others (e.g., proton pump inhibitors that can interfere with nutrient absorption).
• Eat what works for you—especially as you age. For example, the elderly should often avoid lactose in milk products and should be careful to ingest enough vitamins and minerals, especially vitamins B-12 and D.
• In life, there are often special situations, such as early pregnancy, where special nutritional needs arise (e.g., folate).

Acknowledgements

I wish to thank Michiko Spector for her help in preparation of this manuscript.

Notes

1. Taubes, G. 2007. Good Calories, Bad Calories. New York, Alfred A Knopf.
2. Taubes, G. 2007. “Do We Really Know What Makes Us Healthy?” New York Times Magazine, p. 52, Sept. 16.
3. Spector, R., and E.S. Vesell. 2000. “The Pursuit of Clinical Truth: Role of Epidemiology/Observation Studies.” Journal of Clinical Pharmacology 40: 1205-1210.
4. Spector, R., and E.S. Vesell. 2006. “Pharmacology and Statistics: Recommendations to Strengthen a Productive Partnership.” Pharmacology 78: 113-122.
5. Spector, R., and E.S. Vesell. 2002. “Which Studies of Therapy Merit Credence? Vitamin E and Estrogen Therapy as Cautionary Examples.” Journal of Clinical Pharmacology 42: 1-8.
6. Willett, W.C. 2005. Eat, Drink, and Be Healthy. New York: Free Press.
7. Tatsioni, A., N.G. Bonitsis, and J.P.A. Ioannidis. 2007. “Persistence of Contradicted Claims in the Literature.” Journal of the American Medical Association 298: 2517-2526.
8. Spector, R., and E.S. Vesell. 2006 “The Power of Pharmacological Sciences: The Examples of Proton Pump Inhibitors.” Pharmacology 76: 148-156.
9. Hurley, D. 2006. Natural Causes. New York: Broadway Books.
10. Spector, R., and C. Johanson. 2006. “Micronutrient and Urate Transport in Choroid Plexus and Kidney: Implications for Drug Therapy.” Pharmaceutical Research 23: 2515-2524.
11. Spector, R., and C. Johanson. 2007. “Vitamin Transport and Homeostasis in Mammalian Brain: Focus on Vitamins B and E.” Journal of Neurochemistry 103: 425-438.
12. Byers, T. 2006. “Overweight and Mortality among Baby Boomers-Now We’re Getting Personal.” New England Journal of Medicine 355: 758-760.
13. Spector, R., and E.S. Vesell. 2006. “The Heart of Drug Discovery and Development: Rational Target Selection.” Pharmacology 77: 85-92.
14. Moloo, J. 2008. “Dietary Supplements Don’t Prevent Cognitive Decline, CVD, or Infections.” Journal Watch 28: 7-8.
15. Yaffe, K. 2007. “Antioxidants and Prevention of Cognitive Decline: Does Duration of Use Matter?” Archives of Internal Medicine 167: 2167-2168.
16. Peters, U., M.F. Leitzmann, N. Chatterjee, et al. 2007. “Serum Lycopene, Other Carotenoids, and Prostate Cancer Risk: A Nested Case-Control Study in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.” Cancer Epidemiological Biomakers and Prevention 16: 962-968.
17. Kang J.H., N. Cook, J. Manson, et al. 2006. “A Randomized Trial of Vitamin E Supplementation and Cognitive Function in Women.” Archives of Internal Medicine 166: 2462-2468.
18. Espeland, M.A., and V.W. Henderson. 2006. “Preventing Cognitive Decline in Usual Aging.” Archives of Internal Medicine 166: 2433-2434.
19. Jamison, R.L., P. Hartigan, J.S. Kaufman, et al. 2007. “Effect of Homocysteine Lowering on Mortality and Vascular Disease in Advanced Chronic Kidney Disease and End-stage Renal Disease.” Journal of the American Medical Association 298: 1163-1170.
20. Cook, N. R., C. M. Albert, M. Gaziano, et al. 2007. “A Randomized Factorial Trial of Vitamins C and E and Beta Carotene in the Secondary Prevention of Cardiovascular Events in Women.” Archives of Internal Medicine 167: 1610-1618.
21. Brunner, E. 2006. “Oily Fish and Omega 3 Fat Supplements.” British Medical Journal 332: 739-740.
22. Gardner, C.D., A. Kiazand, S. Alhassan, et al. 2007. “Comparison of the Atkins, Zone, Ornish, and LEARN Diets for Change in Weight and Related Risk Factors among Overweight Premenopausal Women.” Journal of the American Medical Association 297: 969-977.
23. . Katan, M.B. 2009. “Weight-Loss Diets for the Prevention and Treatment of Obesity.” New England Journal of Medicine 360: 923-925.

In general, an overriding purpose of all science is to find the truth (Table 1). ^1-3 To accomplish this goal, science, including nutritional research, generally splits its work into three categories: work that describes and classifies, work that explains, and work that predicts. In clinical nutrition, which works extensively in all three categories, acceptance of a statement as “true” requires satisfaction of both definitions given in Table 1. To obtain the truth, a series of assumptions must be made (Table 2). See notes 3-6 for a further discussion of these assumptions and their rationale. Based on their “track records,” the nutritional and medical sciences, although fallible, are capable of approaching and even finding the truth only if rigorous scientific methods are used.^4-7

The complex and difficult problem of causality is central to our understanding of nutrition research.^4-8 A cause is defined as “that factor which is possible or convenient for us to alter in order to produce or prevent an effect. This concept contains two components: production of an effect and an understanding of its mechanisms.”^{5, 6, 8}To understand current concepts of causality, it is helpful to briefly review historical thinking about it (Table 3). Aristotle believed that bodies in motion required constant force (efficient cause) to keep them moving, that the seed contained the adult (teleological cause). After more than 2,000 years, Newton overturned Aristotle in physics with the concept of inertia. Hume further advanced our understanding by postulating that our notion of causality depends on well-documented associations. Partially correct, Kant believed the mind (brain) imposes notions of time, extension, and causality on nature.

More recently, the concepts of necessary and sufficient cause and Koch’s postulates were clearly delineated. Finally, for many situations (e.g., high cholesterol as a “cause” of atherosclerosis, which leads to heart disease and stroke) the idea of contributory causality emerged.^4-6 (In the case of human atherosclerosis, the “cause” is thought to be due to many factors, including cholesterol, macrophages, platelets, lipoproteins, cytokines, leukotrienes, etc. There is not just a single cause.) Contributory causes are sometimes termed precipitating, predisposing, or sustaining causes and are particularly relevant in nutrition research.^4-8 Moreover, the concept of contributory causality often requires statistical thinking and its attendant science, since not everyone with the “cause” (e.g., high cholesterol) develops disease nor does everyone lacking the “cause” fail to develop disease.^4-8 Therefore, because of the nature of contributory causality, large, randomized, long-term controlled clinical trials, especially when effects are modest or slow, are sometimes required to establish the value of certain interventions, e.g., lowering serum cholesterol with diet and/or drugs.^{4-6, 8}

In general, there are three main types of studies in adult human nutritional research to establish causality as shown in Table 4. All three types can play an important role where appropriate. For example, anecdotes can occasionally be definitive. The remarkable responses of unconscious thiamine-deficient patients (with Wernicke’s encephalopathy) to intravenous thiamine (vitamin B1) or comatose hypoglycemic patients to intravenous glucose do not require fancy statistical analyses to see that the intervention (intravenous thiamine or glucose, respectively) is the variable causatively responsible for the response of the patient’s awakening. These are two straightforward examples of necessary and sufficient causality at work. However, many problems in nutrition involve contributory causality and require more complex methods.

General evidentiary requirements in clinical nutrition to prove hypotheses of the type “A causes B” are shown in Table 5.^{4, 6} To satisfy these criteria, epidemiological/observation studies (EOS; Table 4) are often employed specifically to determine whether an association exists between two variables (e.g., an outcome and another variable) and sometimes whether the association is causally related.^3-8 As noted above, in EOS, we are generally testing a hypothesis retrospectively in a case control or prospectively in some cohort studies. (For example, in a case-control, cross-sectional, or cohort study, those with a certain beneficial effect or disease [outcome] may be questioned about the use of a certain food or supplement [putative cause] and compared with controls. When an apparent association between the outcome and putative cause emerges, then the odds of developing the outcome can be calculated in those with the putative cause versus those without. If the association is strong, a causal relationship between the putative cause and outcome is often [frequently incorrectly] assumed.)^{2-4, 6} Of course, the fundamental problem with EOS is they are not randomized. ⁴ Without randomization, one can never be sure the controls are the same as the “experimentals” (e.g., those with the outcome) in everything else except the one variable (the cause) of interest. Therefore, EOS are subject to bias and confounding. Moreover, when it is clear that the two groups are not comparable, attempts to correct the imbalances after the fact are fraught with problems. In the end, often just guesswork or other unproven hypotheses are applied to already questionable data (see below under statistics).

Many years ago, Hill published criteria for deciding causation when association occurs in EOS (Table 6). ^3-5Hill pointed out the need for employing these criteria, especially the strength of associations, including dose-response relationships, when trying to establish causation. ³(In philosophy, this is now termed manipulability theory and is an updating of Mill’s Method of Concomitant Variation.) Hill was concerned about the potential to obtain misleading associations and even worse, false causal associations, unless his criteria were employed. Hill also pointed out that you cannot use statistical analyses in EOS because they are not randomized and hence do not satisfy a key assumption on which all comparative statistical analyses are based (see below). (Obviously, in addition to the criteria listed in Table 6, the study must be properly and honestly performed, not just the result of “data dredging.”)3-5 Perhaps the best example of the success of the Hill approach is the relationship between smoking and cancer of the lungs. In the case of smoking, heavy smoking “causes” a tenor twentyfold increase in lung cancer and there is a “dose-response” relationship. ^3-5 Most of the rest of the criteria in Table 6 are also satisfied. Another example is the spread of papilloma virus (that causes cervical cancer) through sexual activity. However, in many alleged “nutritional causal relationships” based on EOS, the relative risk is less than two, and the attendant statistical analyses are not valid. (See below.)4, 5

In general, the most powerful method to establish the truth of many nutritional hypotheses, when contributory causality is postulated, is the prospective, randomized, controlled trial whose methodological components are shown in Table 7. ^{2-5, 6} This type of trial is the “gold standard” used by regulatory bodies worldwide, including the U.S. FDA for licensure of nutritional claims and drugs. ^{3-5, 6} Such trials can focus on one hypothetically causal variable. (A discussion of the important roles of randomized withdrawal and rechallenge trials in obtaining nutritional truths is beyond the scope of this article [see note 3]). In most prospective, randomized clinical trials (Table 7), the hypothesis tested is that no difference exists in a single-outcome variable (e.g., alive or dead) between control (often placebo) and experimental treatment (e.g., a nutritional intervention like megavitamin E), the so-called null hypothesis. This can be either an efficacy or safety hypothesis. The statistical probability of the outcome (p-value) is calculated assuming the null hypothesis is true. If the p-value of the comparison is 0.05 or less and the trial has sufficient power, the null hypothesis is unlikely to be true. ⁴The smaller the p-value, the less likely the truth of the null hypothesis. Ideally, whenever possible, these trials are blinded; neither sponsor, patient, nor investigator knows who receives which treatment until the study is finished and all the data are cleaned and “locked” in preparation for unblinding. If enough persons are included in the clinical trial, randomization (and the blinding processes if employed) minimizes or eliminates the chance for bias, i.e., baseline differences between the groups (see below). Although the prospective, randomized, controlled clinical trial, especially when blinded, is presently the most powerful method for approaching or finding the truth about contributory causality in clinical nutrition and medicine, regulatory authorities usually require two replicate trials before licensure. ^{2-5, 6} This, in part, is because when results are of borderline statistical significance (i.e., p just less than 0.05), there is a reasonable chance that an identical repeat of the clinical trial will not show a statistically significant (p < 0.05) result. The probability of two consistent replicate trials (both p < 0.05) being incorrect, however, is very low. ^{4, 6} A single, large, blinded, controlled, randomized nutritional or clinical trial that is highly statistically significant (p < .001) is also likely to be correct. ⁴ Of course, the nutritional and clinical (as opposed to statistical) significance of the results depends on the importance of the hypothesis tested, the choice of comparator, and the quantitative size of the difference. When these criteria have been met, few mistakes in ascertaining the truth of the hypotheses tested have occurred. It is also worth noting that the FDA generally demands “substantial” scientific evidence for both safety and efficacy before approving and allowing claims. Finally, extrapolation of the results of successful trials to populations is only reasonable when the participants in the trial mirror the population.

Another critical point is the nature of the outcome variable chosen. What we really want to know are outcomes that are important. For example, in cardiovascular disease trials, we want to prevent angina, heart attacks, strokes, and death. So-called “surrogate” outcomes like serum cholesterol or blood homocysteine are scientifically interesting but can be very misleading. For example, it is not always true that lowering serum cholesterol leads to better outcomes. In fact, lowering cholesterol with the drug clofibrate led to more disease, not less. Thus, the cholesterol hypothesis is that although there is no doubt that lowering cholesterol with statin drugs is highly beneficial in certain populations,6, 7these drugs (statins) have many other effects and it is not clear whether lowering cholesterol or the other effects of these drugs or both leads to less morbidity (heart attacks and strokes) and lower mortality. ^{6, 7, 9}

Statistical Issues

Probability concepts and statistical thinking play an important role in nutritional research (see Table 8). ⁴ As noted above, if randomization (defined in Table 9) is not a part of comparative hypothesis testing, a crucial assumption of statistical usage is not met, and application of statistical tests is chancy and pseudoscientific because, as noted above, potential consequences of non-randomization are bias and confounding (Table 9). ^{3, 4} There are two general types of bias: intentional bias, in which the investigator’s mind has predetermined what is happening, versus unintentional types. ^{3, 4} Over twenty types of unintentional bias have been documented in EOS. ^{3, 4} Because of these problems of non-randomization, bias, and confounding (Table 9), EOS (Table 4) can only occasionally establish causality fairly conclusively (e.g., smoking and lung cancer or sexual activity and papilloma virus infections) as noted above.

Moreover, in many EOS nutrition trials, the measurement instruments are un-validated or poorly validated (e.g., questionnaires about diet, vitamin use, etc.; Table 9). ^{3, 5}The use of poorly validated or un-validated measurement instruments is another reason for the poor track record of many EOS. ^{1-5, 10}

Finally, the notion of falsification in Table 9 requires comment. Popper and others noted how difficult it is to verify certain propositions (e.g., all swans are white), as Hume emphasized centuries ago, since not every swan can be assessed. ^4-6 Only one black swan will disprove the proposition. Verification is especially difficult in testing contributory causality. Popper argued successfully that in all science falsification is easier to understand and embrace than verification. Therefore, nutritional and pharmacological research is often oriented toward falsifying the null hypothesis. The FDA and other regulatory bodies support this approach. Moreover, as in all nutritional and medical research, subtle undefined and unknown confounding variables may still exist.

Thus, in EOS, the lack of randomization, the frequent use of inadequate instruments, and the retrospective nature of hypothesis testing in case-control and cross-sectional studies can often be expected to be problematic with bias, confounding, and erroneous associations and conclusions. This is not just a theoretical concern; in fact, this often happens. ^{3-5, 10} Many examples of claims strongly supported by EOS have subsequently been shown erroneous in large, prospective, blinded, randomized comparative trials. ^{3-5, 6, 7, 11-18} Thus, unless the Hill criteria (Table 6) are met in EOS trials, EOS trial associations and conclusions must be considered, at best, hypothesis-generating. ^{1-5, 10} In other words, one never knows which EOS might be correct and which ones are “false or misleading or non-causal” associations. Moreover, in many cases, there were strong a priori reasons to think the results of the EOS were unlikely to be correct. For example, it was extremely unlikely that mega-vitamin supplements (in non-deficient people) would affect cognitive decline notwithstanding the positive EOS19, 20; there was never biological plausibility (Table 6) for such hypotheses.

In summary, the use of the appropriate methods and statistical analyses in adult nutrition research are critical for finding the truth. Without them, nutrition research and practice are often harmful guesswork or pseudoscience.

Notes

1. Taubes, G. 2007. Good Calories, Bad Calories. New York, Alfred A. Knopf.
2. Taubes, G. 2007. “Do We Really Know What Makes Us Healthy?” New York Times Magazine, p. 52, Sept. 16.
3. Spector, R., and E.S. Vesell. 2000. “The Pursuit of Clinical Truth: Role of Epidemiology/Observation Studies.” Journal of Clinical Pharmacology 40: 1205–1210.
4. Spector, R., and E.S. Vesell. 2006. “Pharmacology and Statistics: Recommendations to Strengthen a Productive Partnership.” Pharmacology 78: 113–122.
5. Spector, R., and E.S. Vesell. 2002. “Which Studies of Therapy Merit Credence? Vitamin E and Estrogen Therapy as Cautionary Examples.” Journal of Clinical Pharmacology 42: 1–8.
6. Spector, R., and E.S. Vesell. 2006 “The Power of Pharmacological Sciences: The Examples of Proton Pump Inhibitors.” Pharmacology 76: 148–156.
7. Spector, R., and E.S. Vesell. 2006. “The Heart of Drug Discovery and Development: Rational Target Selection.” Pharmacology 77: 85–92.
8. Woodward, J. 2003. Making Things Happen: A Theory of Causal Explanation. New York; Oxford, 2003
9. Taubes, G. 2008. “What’s Cholesterol Got to Do With It?” The New York Times, p.18, Jan. 27.
10. Tatsioni, A., N.G. Bonitsis, and J.P.A. Ioannidis. 2007. “Persistence of Contradicted Claims in the Literature.” Journal of the American Medical Association 298: 2517–2526.
11. Moloo, J. 2008. “Dietary Supplements Don’t Prevent Cognitive Decline, CVD, or Infections.” Journal Watch 28: 7–8.
12. Yaffe, K. 2007. “Antioxidants and Prevention of Cognitive Decline: Does Duration of Use Matter?” Archives of Internal Medicine 167: 2167–2168.
13. Peters, U., M.F. Leitzmann, N. Chatterjee, et al. 2007. “Serum Lycopene, Other Carotenoids, and Prostate Cancer Risk: A Nested Case- Control Study in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.” Cancer Epidemiological Biomakers and Prevention 16: 962–968.
14. Kang, J.H., N. Cook, J. Manson, et al. 2006. “A Randomized Trial of Vitamin E Supplementation and Cognitive Function in Women.” Archives of Internal Medicine 166: 2462–2468.
15. Espeland, M.A., and V.W. Henderson. 2006. “Preventing Cognitive Decline in Usual Aging.” Archives of Internal Medicine 166: 2433–2434.
16. Jamison, R.L., P. Hartigan, J.S. Kaufman, et al. 2007. “Effect of Homocysteine Lowering on Mortality and Vascular Disease in Advanced Chronic Kidney Disease and End-Stage Renal Disease.” Journal of the American Medical Association 298: 1163–1170.
17. Cook, N.R., C.M. Albert, M. Gaziano, et al. 2007. “A Randomized Factorial Trial of Vitamins C and E and Beta Carotene in the Secondary Prevention of Cardiovascular Events in Women.” Archives of Internal Medicine 167: 1610–1618.
18. Brunner, E. 2006. “Oily Fish and Omega 3 Fat Supplements.” British Medical Journal 332: 739–740.
19. Spector, R., and C. Johanson. 2006. “Micronutrient and Urate Transport in Choroid Plexus and Kidney: Implications for Drug Therapy.”
20. Spector, R., and C. Johanson. 2007. “Vitamin Transport and Homeostasis in Mammalian Brain: Focus on Vitamins B and E.” Journal of Neurochemistry. 103: 425–438.

Tables