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Tuesday, September 30, 2014

Transcranial Magnetic Stimulation Offers Hope for Treatment-Resistant Depression

Therese Borchard
Sanity Break

Help for depression and anxiety


Transcranial Magnetic Stimulation Offers Hope for Treatment-Resistant Depression

By Therese Borchard

Published Sep 29, 2014

In December of 2012, Stephanie S. was taking 300 mgs of sertraline (Zoloft), 300 mgs of (bupropion Hcl) Wellbutrin, 300 mgs of trazodone hydrochloride (Desyrel), 200 mgs of risperidone (Risperdal), and 8 mgs of alprazolam (Xanax), but was as depressed as she has ever been. She had also gained 100 pounds as a side effect of all the medications. Having tried a total of 10 different kinds of drugs with no success, her doctor recommended transcranial magnetic stimulation (TMS), a non-invasive procedure that stimulates nerve cells in the brain with short magnetic pulses. A large electromagnetic coil is placed against the scalp which generates focused pulses that pass through the skull and stimulate the cerebral cortex of the brain, a region that regulates mood. The procedure was approved by the FDA in 2008.

She didn’t feel any difference after 11 treatments, but she can vividly remember the morning after her 12th treatment. She explained:

I woke up… I mean WOKE UP!! I felt so light, instead of feeling weighed down. The sun was brighter. My overall feeling was JOY. This was unfamiliar to me, and I loved it. I came downstairs grinning from ear to ear and just looked at my husband. He knew! I just threw my arms around his neck and laughed. The feeling was indescribable. It was NIRVANA!! I felt better than I had felt before my breakdown. It was MAGICAL! I think that was the first time in my life that I felt pure joy!

She continued and finished the 30 treatments.

Dr. Kira Stein, MD, board certified psychiatrist and medical director of West Coast TMS Institute in Sherman Oaks, Los Angeles, is excited about the success she’s had in treating her patients with TMS. She usually does five sessions a week, for a total of 30 sessions; the entire procedure lasts about six to eight weeks, though some patients may need more treatment to respond.

She estimates that about one-third of TMS patients have a full remission and no longer experience depression symptoms.

One-half of TMS patients respond signficantly, where their depression symptoms are improved by at least 50 percent, but do not reach complete remission. The more depressive cycles they have had in their lives, the more difficult it is to treat them in general.

Dr. Stein’s experience is that TMS success rates are higher when TMS is used as an augmentation strategy for patients who have only partially responded to medication, or who cannot tolerate higher medication doses. She usually recommends a person stay on a dose of maintenance antidepressants and finds that some patients need maintenance TMS treatments to stay well.

The treatment is expensive. Dr. Stein says that each session (and on average people usually require 30) run from $300 to $450, a session; however, more and more insurance companies are picking up at least some of the bill.

Stephanie paid $7,450 out of pocket. Her insurance chipped in $7,000 (the total cost was about $14,000).

Stephanie stayed in remission for a year and a half until a cascade of tragic events, including the suicide of her sister, caused a relapse of depressive symptoms. When different kinds of medication again did little to relieve her pain, she decided to do TMS for a second time.

She’s been participating in the online depression support group I moderate on Facebook. About a month ago, I remember a distinct change in the tone of her posts. They went from being desperate to hopeful, from cynical to curious, and from flat to playful.

“What’s the matter with me?” she asked the group. “On the way to my husband’s work, I’m noticing everything for the first time.”

“I think your TMS treatment is working,” I replied.

“Yes!” she said. “I laughed again!!”

She has eight treatments left, and hopes she continues to laugh for a very long time.

Posted in: Depression


New study reports how TMS treatment works in people with depression

New study reports how TMS treatment works in people with depression

Published on September 30, 2014 at 12:21 PM · No Comments


A new study in Biological Psychiatry reports how magnetic stimulation treatment works

On Star Trek, it is easy to take for granted the incredible ability of futuristic doctors to wave small devices over the heads of both humans and aliens, diagnose their problems through evaluating changes in brain activity or chemistry, and then treat behavior problems by selectively stimulating relevant brain circuits.

While that day is a long way off, transcranial magnetic stimulation (TMS) of the left dorsolateral prefrontal cortex does treat symptoms of depression in humans by placing a relatively small device on a person's scalp and stimulating brain circuits. However, relatively little is known about how, exactly, TMS produces these beneficial effects.

Some studies have suggested that TMS may modulate atypical interactions between two large-scale neuronal networks, the frontoparietal central executive network (CEN) and the medial prefrontal-medial parietal default mode network (DMN). These two functional networks play important roles in emotion regulation and cognition.

In order to advance our understanding of the underlying antidepressant mechanisms of TMS, Drs. Conor Liston, Marc Dubin, and their colleagues conducted a longitudinal study to test this hypothesis.

The researchers used functional magnetic resonance imaging in 17 currently depressed patients to measure connectivity in the CEN and DMN networks both before and after a 25-day course of TMS. They also compared the connectivity in the depressed patients with a group of 35 healthy volunteers.

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TMS normalized depression-related hyperconnectivity between the subgenual cingulate and medial prefrontal areas of the DMN, but did not alter connectivity in the CEN.

Liston, an Assistant Professor at Weill Cornell Medical College, further details their findings, "We found that connectivity within the DMN and between nodes of the DMN and CEN was elevated in depressed individuals compared to healthy volunteers at baseline and normalized after TMS. Additionally, individuals with greater baseline connectivity with subgenual anterior cingulate cortex - an important target for other antidepressant modalities - were more likely to respond to TMS."

These findings indicate that TMS may act, in part, by selectively regulating network-level connectivity.

Dr. John Krystal, Editor of Biological Psychiatry, comments, "We are a long way from Star Trek, but even the current ability to link brain stimulation treatments for depression to the activity of particular brain circuits strikes me as incredible progress."

Dubin, also an Assistant Professor at Weill Cornell Medical College, adds, "Our findings may inform future efforts to develop personalized strategies for treating depression with TMS based on the connectivity of an individual's default mode network. Further, they may help triage to TMS only those patients most likely to respond."

Tuesday, September 23, 2014

Safety of a dedicated brain MRI protocol in patients with a vagus nerve stimulator.

Epilepsia. 2014 Sep 19. doi: 10.1111/epi.12774. [Epub ahead of print]

Safety of a dedicated brain MRI protocol in patients with a vagus nerve stimulator.

de Jonge JC1, Melis GI, Gebbink TA, de Kort GA, Leijten FS.

Author information
  • 1Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.

Although implanted metallic devices constitute a relative contraindication to magnetic resonance imaging (MRI) scanning, the safety of brain imaging in a patient with a vagus nerve stimulator (VNS) is classified as "conditional," provided that specific manufacturer guidelines are followed when a transmit and receive head coil is used at 1.5 or 3.0 Tesla. The aim of this study was to evaluate the safety of performing brain MRI scans in patients with the VNS. From September 2009 until November 2011, 101 scans were requested in 73 patients with the VNS in The Netherlands. Patients were scanned according to the manufacturer's guidelines. No patient reported any side effect, discomfort, or pain during or after the MRI scan. In one patient, a lead break was detected based on device diagnostics after the MRI-scan. However, because no system diagnostics had been performed prior to MR scanning in this patient, it is unclear whether MR scanning was responsible for the lead break. The indication for most scans was epilepsy related. Twenty-six scans (26%) were part of a (new) presurgical evaluation and could probably better have been performed prior to VNS implantation. Performing brain MRI scans in patients with an implanted VNS is safe when a modified MRI protocol is followed.

Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.


Epilepsy; Magnetic resonance imaging; Patient safety; Vagus nerve stimulator

[PubMed - as supplied by publisher]
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Monday, September 22, 2014

Evidence supports deep brain stimulation for obsessive-compulsive disorder



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Contact: Connie Hughes
Wolters Kluwer Health

Evidence supports deep brain stimulation for obsessive-compulsive disorder

Bilateral stimulation is effective for OCD that doesn't respond to medications, says new guideline in Neurosurgery

September 22, 2014 – Available research evidence supports the use of deep brain stimulation (DBS) for patients with obsessive-compulsive disorder (OCD) who don't respond to other treatments, concludes a review in the October issue of Neurosurgery, official journal of the Congress of Neurological Surgeons (CNS). The journal is published by Lippincott Williams & Wilkins, a part of Wolters Kluwer Health.

Based on evidence, two specific bilateral DBS techniques are recommended for treatment of carefully selected patients with OCD, according to a new clinical practice guideline endorsed by the CNS and the American Association of Neurological Surgeons. While calling for further research in key areas, Dr. Clement Hamani of Toronto Western Hospital and coauthors emphasize that patients with OCD symptoms that don't respond to other treatments should continue to have access to DBS.

Deep Brain Stimulation for OCD—What's the Evidence?

Dr. Hamani led a multispecialty expert group in performing a systematic review of research on the effectiveness of DBS for OCD. Deep brain stimulation—placement of electrodes in specific areas of the brain, followed by electrical stimulation of those areas—has become an important treatment for patients with Parkinson's disease and other movement disorders.

Although many patients with OCD respond well to medications and/or psychotherapy, 40 to 60 percent continue to experience symptoms despite treatment. Over the past decade, a growing number of reports have suggested that DBS may be an effective alternative in these "medically refractory" cases.

Dr. Hamani and colleagues were tasked with analyzing the supporting evidence and developing an initial clinical practice guideline for the use of DBS for patients with OCD. The review and guideline development process was sponsored by the American Society of Stereotactic and Functional Neurosurgery and the CNS. Out of more than 350 papers, the reviewers identified seven high-quality studies evaluating DBS for OCD.

Based on that evidence, they conclude that bilateral stimulation (on both sides of the brain) of two brain "targets"—areas called the subthalamic nucleus and the nucleus accumbens—can be regarded as effective treatments for OCD. In controlled clinical trials, both techniques improved OCD symptoms by around 30 percent on a standard rating scale.

While Research Proceeds, well-selected treatment-resistant severe OCD Patients Should Have Access to DBS

That evidence forms the basis for a clinical guideline stating that bilateral DBS is a "reasonable therapeutic option" for patients with severe OCD that does not respond to other treatments. The guideline also notes that there is "insufficient evidence" supporting the use of any type of unilateral DBS target (one side of the brain) for OCD.

The review highlights the difficulties of studying the effectiveness of DBS for OCD—because most patients respond to medical treatment, studies of this highly specialized treatment typically include only small numbers of patients. Dr. Hamani and coauthors identify some priorities for future research: particularly to identify the most effective brain targets and the subgroups of patients most likely to benefit.

Despite the limited evidence base, DBS therapy for OCD has been approved by the Food and Drug Administration under a humanitarian device exemption. Dr. Hamani and coauthors note that various safeguards are in place to ensure appropriate use, and prevent overuse, of DBS for OCD.

While research continues, they believe that functional neurosurgeons should continue to work with other specialists to ensure that patients with severe, medically refractory OCD continue to have access to potentially beneficial DBS therapy.


Click here to read "Deep Brain Stimulation for Obsessive-Compulsive Disorder: Systematic Review and Evidence-Based Guideline Sponsored by the American Society for Stereotactic and Functional Neurosurgery and the Congress of Neurological Surgeons (CNS) and Endorsed by the CNS and American Association of Neurological Surgeons."

About Neurosurgery

Neurosurgery, the Official Journal of the Congress of Neurological Surgeons, is your most complete window to the contemporary field of neurosurgery. Members of the Congress and non-member subscribers receive 3,000 pages per year packed with the very latest science, technology, and medicine, not to mention full-text online access to the world's most complete, up-to-the-minute neurosurgery resource. For professionals aware of the rapid pace of developments in the field, Neurosurgery is nothing short of indispensable.

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Wolters Kluwer Health is a leading global provider of information, business intelligence and point-of-care solutions for the healthcare industry. Serving more than 150 countries worldwide, clinicians rely on Wolters Kluwer Health's market leading information-enabled tools and software solutions throughout their professional careers from training to research to practice. Major brands include Health Language®, Lexicomp®, Lippincott Williams & Wilkins, Medicom®, Medknow, Ovid®, Pharmacy OneSource®, ProVation® Medical and UpToDate®.

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Friday, September 19, 2014

Vagus nerve stimulation for drug-resistant epilepsy: A European long-term study up to 24 months in 347 children.

Epilepsia. 2014 Sep 17. doi: 10.1111/epi.12762. [Epub ahead of print]

Vagus nerve stimulation for drug-resistant epilepsy: A European long-term study up to 24 months in 347 children.

Orosz I1, McCormick D, Zamponi N, Varadkar S, Feucht M, Parain D, Griens R, Vallée L, Boon P, Rittey C, Jayewardene AK, Bunker M, Arzimanoglou A, Lagae L.

Author information
  • 1Department of Neuropediatrics, Children's Hospital, University of Leubeck, Leubeck, Germany.

To gain insight into the long-term impact of vagus nerve stimulation (with VNS Therapy) in children with drug-resistant epilepsy, we conducted the largest retrospective multicenter study to date over an extended follow-up period of up to 24 months.


The primary objective was to assess change in seizure frequency of the predominant seizure type (defined as the most disabling seizure) following VNS device implantation. Treating physicians collected data from patient records from baseline to 6, 12, and 24 months of follow-up.


The analysis population included 347 children (aged 6 months to 17.9 years at the time of implant). At 6, 12, and 24 months after implantation, 32.5%, 37.6%, and 43.8%, respectively, of patients had ≥50% reduction in baseline seizure frequency of the predominant seizure type. The responder rate was higher in a subgroup of patients who had no change in antiepileptic drugs (AEDs) during the study. Favorable results were also evident for all secondary outcome measures including changes in seizure duration, ictal severity, postictal severity, quality of life, clinical global impression of improvement, and safety. Post hoc analyses demonstrated a statistically significant correlation between VNS total charge delivered per day and an increase in response rate. VNS Therapy is indicated as adjunctive therapy in children with focal, structural epilepsies, who for any reason are not good candidates for surgical treatment following the trial of two or more AEDs. Children with predominantly generalized seizures from genetic, structural epilepsies, like Dravet syndrome or Lennox-Gastaut syndrome, could also benefit from VNS Therapy.


The results demonstrate that adjunctive VNS Therapy in children with drug-resistant epilepsy reduces seizure frequency and is well tolerated over a 2-year follow-up period. No new safety issues were identified. A post hoc analysis revealed a dose-response correlation for VNS in patients with epilepsy.

Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.


Clinical trial; Epilepsy; Pediatrics; Quality of life; Vagus nerve stimulation

[PubMed - as supplied by publisher]

Wednesday, September 17, 2014

Response to TMS Sustained in Depression

Medscape Medical News > Psychiatry

Response to TMS Sustained in Depression

Pam Harrison

September 17, 2014



The final analysis of a study evaluating transcranial magnetic stimulation (TMS) confirms that the majority of patients with resistant depression who respond to TMS in the acute setting continue to have a sustained response for a period of 1 year, an observational trial shows.

David Dunner, MD, director, Center for Anxiety and Depression, Mercer Island, Washington, and colleagues reported that 68% of 257 patients who had received TMS during the acute treatment phase had improved by the end of the 12-month follow-up and that 45% had experienced complete remission at 1 year.

"These are patients with treatment-resistant depression who are difficult to treat, who generally do not get better easily. TMS not only got people better with the usual course of about 30 treatments in the acute treatment phase, but we showed that the benefit was maintained over a 1-year period in the majority of patients who improved," Dr. Dunner told Medscape Medical News.

Courtesy of Neuronetics, Inc.

"So I view TMS as a treatment for people who have a new depression and who have a history of failing 3 or 4 prior treatments for depression, where it is unlikely that the antidepressant is going to work. In that population, I think we get good results, and the results justify the use of TMS and the cost of treatment as well."

The final results of the observational study were published online on September 16 in the Journal of Clinical Psychiatry. Preliminary long-term results were first reported from the American Psychiatric Association meeting in 2013 by Medscape Medical News. The study was supported by Neuronetics Inc.

Long-term Results

As investigators previously reported ( Depress Anxiety. 2012;29:587-596), 62% of patients had achieved symptomatic improvement, and 41% had achieved a complete remission by the end of the acute treatment phase.

Wednesday, September 10, 2014

It Ain't Necessarily So: Why Much of the Medical Literature Is Wrong

It Ain't Necessarily So: Why Much of the Medical Literature Is Wrong

Christopher Labos, MD CM, MSc, FRCPC

September 09, 2014


In 1897, eight-year-old Virginia O'Hanlon wrote to the New York Sun to ask, "Is there a Santa Claus?"[1] Virginia's father, Dr. Phillip O'Hanlon, suggested that course of action because "if you see it in the Sun, it's so." Today many clinicians and health professionals may share the same faith in the printed word and assume that if it says it in the New England Journal of Medicine (NEJM) or JAMA or The Lancet, then it's so.

Putting the existence of Santa Claus aside, John Ioannidis[2] and others have argued that much of the medical literature is prone to bias and is, in fact, wrong.

Given a statistical association between X and Y, most people make the assumption that X caused Y. However, we can easily come up with 5 other scenarios to explain the same situation.

1. Reverse Causality

Given the association between X and Y, it is actually equally likely that Y caused X as it is that X caused Y. In most cases, it is obvious which variable is the cause and which is the effect. If a study showed a statistical association between smoking and coronary heart disease (CHD), it would be clear that smoking causes CHD and not that CHD makes people smoke. Because smoking preceded CHD, reverse causality in this case is impossible. But the situation is not always that clear-cut. Consider a study published in the NEJM that showed an association between diabetes and pancreatic cancer.[3] The casual reader might conclude that diabetes causes pancreatic cancer. However, further analysis showed that much of the diabetes was of recent onset. The pancreatic cancer preceded the diabetes, and the cancer subsequently destroyed the insulin-producing islet cells of the pancreas. Therefore, this was not a case of diabetes causing pancreatic cancer but of pancreatic cancer causing the diabetes.

Mistaking what came first in the order of causation is a form of protopathic bias.[4] There are numerous examples in the literature. For example, an assumed association between breast feeding and stunted growth, [5] actually reflected the fact that sicker infants were preferentially breastfed for longer periods. Thus, stunted growth led to more breastfeeding, not the other way around. Similarly, an apparent association between oral estrogens and endometrial cancer was not quite what it seemed.[6] Oral estrogens may be prescribed for uterine bleeding, and the bleeding may be caused by an undiagnosed cancer. Therefore, when the cancer is ultimately diagnosed down the road, it will seem as if the estrogens came before the cancer, when in fact it was the cancer (and the bleeding) that led to the prescription of estrogens. Clearly, sometimes it is difficult to disentangle which factor is the cause and which is the effect.

2. The Play of Chance and the DICE Miracle

Whenever a study finds an association between 2 variables, X and Y, there is always the possibility that the association was simply the result of random chance.

Most people assess whether a finding is due to chance by checking if the P value is less than .05. There are many reasons why this the wrong way to approach the problem, and an excellent review by Steven Goodman[7] about the popular misconceptions surrounding the P value is a must-read for any consumer of medical literature.

To illustrate the point, consider the ISIS-2 trial,[8] which showed reduced mortality in patients given aspirin after myocardial infarction. However, subgroup analyses identified some patients who did not benefit: those born under the astrological signs of Gemini and Libra; patients born under other zodiac signs derived a clear benefit with a P value < .00001. Unless we are prepared to re-examine the validity of astrology, we would have to admit that this was a spurious finding due solely to chance. Similarly, Counsell et al. performed an elegant experiment using 3 different colored dice to simulate the outcomes of theoretical clinical trials and subsequent meta-analysis.[9] performed an elegant experiment using 3 different colored dice to simulate the outcomes of theoretical clinical trials and subsequent meta-analysis. Students were asked to roll pairs of dice, with a 6 counting as patient death and any other number correlating to survival. The students were told that one dice may be more "effective" or less effective (ie, generate more sixes or study deaths). Sure enough, no effect was seen for red dice, but a subgroup of white and green dice showed a 39% risk reduction (P = .02). Some students even reported that their dice were "loaded." This finding was very surprising because Counsell had played a trick on his students and used only ordinary dice. Any difference seen for white and green dice was a completely random result.

The Frequency of False Positives

It is sometimes humbling and fairly disquieting to think that chance can play such a large role in the results of our analyses. Subgroup analyses, as shown above, are particularly prone to spurious associations. Most researchers set their significance level or rate of type 1 error at 5%. However, if you perform 2 analyses, then the chance of at least one of these tests being "wrong" is 9.75%. Perform 5 tests, and the probability becomes 22.62%; and with 10 tests, there is a 40.13% of at least 1 spurious association even if none of them are actually true. Because most papers present many different subgroups and composite endpoints, the chance of at least one spurious association is very high. Often, the one spurious association is published, and the other negative tests never see the light of day.[10]

There is a way to guard against such spurious findings: replication. Unfortunately, the current structure of academic medicine does not favor the replication of published results,[11] and several studies have shown that many published trials do not stand up to independent verification and are likely false positives.[12,13] In 2005, John Ioannidis published a review of 45 highlighted studies in major medical journals. He found that 24% were never replicated, 16% were contradicted by subsequent research, and another 16% were shown to have smaller effect sizes than originally reported. Less than half (44%) were truly replicated.

The frequency of these false-positive studies in the published literature can be estimated to some degree.[2] Consider a situation in which 10% of all hypotheses are actually true. Now consider that most studies have a type 1 error rate (the probability of claiming an association when none exists [ie, a false positive]) of 5% and a type 2 error rate (the probability of claiming there is no association when one actually exists [ie, a false negative)] of 20%, which are the standard error rates presumed by most clinical trials. This allows us to create the following 2x2 table.

By plugging in the numbers above:

This would imply that of the 125 studies with a positive finding, only 80/125 or 64% are true. Therefore, one third of statistically significant findings are false positives purely by random chance. That assumes, of course, that there is no bias in the studies, which we will deal with presently.

3. Bias: Coffee, Cellphones, and Chocolate

Bias occurs when there is no real association between X and Y, but one is manufactured because of the way we conducted our study. Delgado-Rodriguez and Llorca[4] identified 74 types of bias in their glossary of the most common biases, which can be broadly categorized into 2 main types: selection bias and information bias.

One classic example of selection bias occurred in 1981 with a NEJM study showing an association between coffee consumption and pancreatic cancer.[15] The selection bias occurred when the controls were recruited for the study. The control group had a high incidence of peptic ulcer disease, and so as not to worsen their symptoms, they drank little coffee. Thus, the association between coffee and cancer was artificially created because the control group was fundamentally different from the general population in terms of their coffee consumption. When the study was repeated with proper controls, no effect was seen.[16]

Information bias, as opposed to selection bias, occurs when there is a systematic error in how the data are collected or measured. Misclassification bias occurs when the measurement of an exposure or outcome is imperfect; for example, smokers who identify themselves as nonsmokers to investigators or individuals who systematically underreport their weight or overreport their height.[17] A special situation, known as recall bias, occurs when subjects with a disease are more likely to remember the exposure under investigation than controls. In the INTERPHONE study, which was designed to investigate the association between cell phones and brain tumors, a spot-check of mobile phone records for cases and controls showed that random recall errors were large for both groups with an overestimation among cases for more distant time periods.[18] Such differential recall could induce an association between cell phones and brain tumors even if none actually exists.

An interesting type of information bias is the ecological fallacy. The ecological fallacy is the mistaken belief that population-level exposures can be used to draw conclusions about individual patient risks.[4] A recent example of the ecological fallacy, was a tongue-in-cheek NEJM study by Messerli[19} showing that countries with high chocolate consumption won more Nobel prizes. The problem with country-level data is that countries don't eat chocolate, and countries don't win Nobel prizes. People eat chocolate, and people win Nobel prizes. This study, while amusing to read, did not establish the fundamental point that the individuals who won the Nobel prizes were the ones actually eating the chocolate.[20]

Another common ecological fallacy is the association between height and mortality. There are a number of reviews suggesting that shorter stature is associated with a longer life span.[21] However, most of these studies looked at country-level data. Danes are taller than Italians and also have more coronary heart disease. However, if you look at twins[22] or individuals within the same country,[23] you see the opposite association -- namely, it is the shorter individuals who have more heart disease. Again, the fault lies in looking at countries rather than individuals.

4. Confounding

Confounding, unlike bias, occurs when there really is an association between X and Y, but the magnitude of that association is influenced by a third variable. Whereas bias is a human creation, the product of inappropriate patient selection or errors in data collection, confounding exists in nature.[24]

For example, diabetes confounds the relationship between renal failure and heart disease because it can lead to both conditions. Although patients with renal failure are at higher risk for heart disease, failing to account for the inherent risk of diabetes makes that association seem stronger than it actually is.

Confounding is a problem in every observational study, and statistical adjustment cannot always eliminate it. Even some of the best observational trials fall victim to confounding. Hormone replacement therapy was long thought to be protective for cardiac disease[25] until the Women’s Health Initiative randomized trial refuted that notion.[26] Despite the best attempts at statistical adjustment, there can always be residual confounding. However, simply putting more variables into a multivariate model is not necessarily a better option. Overadjusting can be just as problematic, and adjusting for unnecessary variables can lead to biased results.[27,28]

Real-World Randomization

Confounding can be dealt with through randomization. When study subjects are randomly allocated to one group or another purely by chance, any confounders (even unknown confounders) should be equally present in both the study and control group. However, that assumes that randomization was handled correctly. A 1996 study sought to compare laparoscopic vs open appendectomy for appendicitis.[29] The study worked well during the day, but at night the presence of the attending surgeon was required for the laparoscopic cases but not the open cases. Consequently, the on-call residents, who didn't like calling in their attendings, adopted a practice of holding the translucent study envelopes up to the light to see if the person was randomly assigned to open or laparoscopic surgery. When they found an envelope that allocated a patient to the open procedure (which would not require calling in the attending and would therefore save time), they opened that envelope and left the remaining laparoscopic envelopes for the following morning. Because cases operated on at night were presumably sicker than those that could wait until morning, the actions of the on-call team biased the results. Sicker cases preferentially got open surgery, making the outcomes of the open procedure look worse than they actually were.[30] So, though randomized trials are often thought of as the solution to confounding, if randomization is not handled properly, confounding can still occur. In this case, an opaque envelope would have solved the problem.

5. Exaggerated Risk

Finally, let us make the unlikely assumption that we have a trial where nothing went wrong, and we are free of all of the problems discussed above. The greatest danger lies in our misinterpretation of the findings. A report in the New England Journal of Medicine reported that African Americans were 40% less likely to be sent for an angiogram than their white counterparts.[31] The report generated considerable media attention at the time, but a later article by Schwartz et al.[32] pointed out that the results were overstated. Had the authors used a risk ratio instead of an odds ratio, the result would have been 7% instead of 40%, and it's unlikely that the paper would have been given such prominence. Choosing the correct statistical test can be difficult. Nearly 20 years ago. Sackett and colleagues[33] proclaimed "Down with odds ratios!"[33] and yet they remain frequently used in the literature.

Another major problem is the use of relative risks vs absolute risks. Although the latter are clearly preferable, one review of almost 350 studies found that 88% never reported the absolute risk.[34] Furthermore, overreliance on relative risks can be very misleading. Baylin and colleagues[35] reported that the relative risk for myocardial infarction in the hour after drinking a cup of coffee was 1.5 (ie, a 50% increase). This rather concerning finding was taken up by Poole in a bitingly satirical letter to the editor,[36] in a bitingly satirical letter to the editor, where he calculated that the relative risk of 1.5 translated to an absolute risk of 1 heart attack for every 2 million cups of coffee. Clearly, well-done studies have to be put in clinical context, and it is paramount to remember that statistical significance does not imply clinical significance.

Why Bother?

With all of the different ways that clinical trials can go wrong, one might wonder why we bother at all. Unlike little Virginia, who was prepared to believe whatever she saw in the newspaper, we have become, if not cynics, then at least skeptics when it comes to our published research. But skepticism is a good thing and makes us challenge what we think we know in favor of what we can prove. Without this skepticism, we would still be prescribing hormone replacement therapy to prevent heart disease in women, giving class I anti-arrhythmics to cardiac patients after myocardial infarction, and prescribing COX-2 inhibitors with reckless abandon.

As Dr. Fiona Godlee summed up in her BMJ editorial on evidence-based medicine, “[it’s a] flawed system but still the best we’ve got.”[37]

  1. Berman R. Virginia O'Hanlon's home to be turned into school. December 16, 2005. Accessed July 24, 2014.

  2. Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2:e124.

  3. Gullo L, Pezzilli R, Morselli-Labate AM; Italian Pancreatic Cancer Study Group. Diabetes and the risk of pancreatic cancer. N Engl J Med. 1994;331:81-84. Abstract

  4. Delgado-Rodríguez M, Llorca J. Bias. J Epidemiol Community Health. 2004;58:635-641. Abstract

  5. Marquis GS, Habicht JP, Lanata CF, Black RE, Rasmussen KM. Association of breastfeeding and stunting in Peruvian toddlers: an example of reverse causality. Int J Epidemiol. 1997;26:349-356. Abstract

  6. Horwitz RI, Feinstein AR. Analysis of clinical susceptibility bias in case-control studies. Analysis as illustrated by the menopausal syndrome and the risk of endometrial cancer. Arch Intern Med. 1979;139:1111-1113. Abstract

  7. Goodman S. A dirty dozen: twelve P-value misconceptions. Semin Hematol. 2008;45:135-140. Abstract

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  9. Counsell CE, Clarke MJ, Slattery J, Sandercock PA. The miracle of DICE therapy for acute stroke: fact or fictional product of subgroup analysis? BMJ. 1994;309:1677-1681. Abstract

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