Archive for the 'Research issues' category

Truth and Consequences

Apr 26 2016 Published by under [Medicine&Pharma], Research issues

This morning I saw a blurb in one of my newsfeeds about "potential new treatment target for deadly brain cancer."

It was indeed a new study on the cellular biology of glioblastomas, the type of cancer in my husband's head. We just finished the first round of radiation and chemotherapy. The next 4 weeks will be blissfully treatment-free. Instead, we will devote his time to weekly fasting lab studies and a whole bunch of doctor appointments. Oh, and he gets to go to the dentist this week.

This discovery involves the basic cell biology of these cancer cells, and may help explain why they are so resistant to treatment. They interview the author of the study, Dr. Arezu Jahani-Asl, who explains why she chose to study glioblastoma:

"The fact that most patients with these brain tumours live only 16 months is just heartbreaking,"

That's a particularly heartbreaking reminder with which to begin my day.

Keep plugging away, scientists. It's only through your efforts that we have hope. We also have no idea who will find the key piece of information that leads to improved survival or even a cure; it may be someone studying insects in the rainforest rather than a neuroscientist looking at this tumor. That's why we need to fund as much science as we can.

So we all can have hope.

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Why We Can't Do a Cancer Moonshot

Jan 15 2016 Published by under Research issues

The moment was beautiful, Obama announcing that Biden would direct our next public effort, a moonshot, to cure cancer. Of course, this will not happen with cancer or any other disease that comes to mind.

First, cancer is more than one disease. It affects multiple organs in multiple ways through multiple mechanisms. Most diseases that kill in the US right now could be described this way. Even diabetes, mostly driven by obesity, probably results from a variety of genetic and environmental mechanisms. If we are talking about a single, well-characterized disorder with a single cause, we might be able to do something in a 12-year window.

The bigger problem is we do not know enough about this stuff. When Sputnik launched, we had the same knowledge base as the Soviets. We understood rocketry and astroscience enough to make a moon landing happen. Sputnik pushed the resources to the project. The basic science and technology was available; it was an incremental, if huge, project.

We are not there with most forms of cancer. We do not understand the basic biology well enough yet.

After discovering insulin, Banting turned to cancer research. He made no inroads there. I can remember Nixon declaring war on cancer shortly after the moon landing. We have come a long way since then, but the battles still rage on.

If we really want to cure diseases, we need to fund a wide variety of research ranging from the most basic sciences to clinical studies. We can never predict what finding will provide the key to a breakthrough, no matter how good we believe our peer-review system may be. It may be in a seemingly unrelated field.

We need sustainable growth of the budgets for the NIH and NSF. That will, someday, help us overcome the multitude of cancers and other disorders that we face.

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Clinical Research: More than an extension of patient care

Apr 24 2014 Published by under Research issues

When I started my first faculty appointment, I planned to have a lab. My techniques could be performed on human or animal specimens, so I could move between the worlds of clinical and basic science research with ease. I got a fairly standard deal for the time - 70% protected time for the lab. By the time you realize that all vacation and meetings come out of that protected time, as does the paperwork and documentation that accompanies clinical practice, that protection really only gives you about half of your time. In my case, that was enough, at least until the NIH budget collapsed in the Great Recession.

Recently, I have heard of new clinicians trying to set up clinical research programs. Now, clinical research does involve patients, but it is not merely an extension of patient care. Clinical research is something completely outside of the realm of usual care. I have seen assistant professors with only 30% protected time written into their contracts to develop a clinical research career! Clinical research also requires as much support as a bench lab. Sure, I needed space and all sorts of expensive equipment for my work; however, I could analyze a rat experiment myself and control a lot of variables. When people get involved, all control flies out the window. This means more statistical support up front in the design phase of a study, as well as more analysis to help control for those unanticipated things that make all studies flawed in some way.

I once pointed this out to a chair who said that if they got a grant with salary support then they could have more protected time. Yes, those grants find their way to deserving faculty who have no time carved out to develop a track record and publications...

I find it disturbing that we set junior faculty up for failure this way, with incredibly unrealistic expectations.

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You Cannot Know Until You Know

May 29 2013 Published by under Research issues

Last night I received an interesting query via twitter:


Many patients in nephrology present with 50-60% of normal kidney function. Even if we can stop the insult that produced this much loss of kidney, at this point the vicious cycle of progression occurs. The kidney tries to adapt to its losses with processes that cause more loss of tissue. In trying to get back to normal, the kidney commits suicide. Over the years, we have discovered ways to slow this process, but we cannot stop it. This is particularly unfortunate, because most people have no symptoms of kidney failure with minimal medication at half of normal function. If we could halt the process at that point, most adults would have relatively normal lives without needing dialysis or transplant! (Since we cannot do this yet, I do not yet know if we could get children to grow and develop acceptably at half of normal function.)

Thus, my answer:


Of course, this is a really broad answer that is likely more clinically oriented than whatever spawned the question. Kidney researchers have been working on progression for as long as I can remember, resulting in our current strategies that slow it down; however, we still do not fully understand the process despite at least two decades of research! And, while I can identify this as a really clinically important area of inquiry, I HAVE NO IDEA WHERE THE BIG BREAKTHROUGH WILL ULTIMATELY COME FROM. If more incremental work in the existing areas will do it, then we may get there in a few years. I suspect the real breakthrough will come out of left field, from completely unexpected directions.

You know, the risky, out-there research that will have more trouble getting funded right now.

It may also come from studies of other organ systems! Other diseases! Other organisms!

I believe this is true for most clinical problems facing us today. We really cannot know what particular basic science piece will lead to therapeutic insights and cures. Who would have thought that studying cilia would help us understand polycystic kidney disease?

That's the real tragedy of the current funding climate. As paylines drop, funding tends to get more conservative with projects having the best chance of "success," defined as fulfilling their hypothesis. This can result in incremental studies which may be valuable, but rarely shift paradigms. Those weird, unexpected results that can impact other fields may be missed completely.

Patch-clamping fruit fly neurons may sound like a ridiculous waste of  money to the general public (and congress), but from a basic science standpoint it could be quite important. If we want cures for diseases, we have to support scientific inquiry, not just clinically-directed research. Our current "best treatments" for the problem of progression arose from studies of South American vipers; I would guess that those investigators had no idea that there would be such practical outcomes from their research.

Let's put it this way: I am a physician-scientist with more than 20 years of experience in the field, and I have no idea what specific basic science questions may lead to the next big breakthrough. Our best hope is to fund as much as we can, all of it if possible. We then need to keep scientists and clinicians engaged, so those random sparks of imagination come together.

The process is messy and disorganized and unpredictable. You cannot script discovery.

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Down with Glam; Up with Fast & Cheap

Apr 03 2013 Published by under Publication, Research issues

A lot of folks are trying to reinvent the way we share research. I cannot remember the last time I read a paper journal; even with traditional publishing models, the dead tree format ends up in the recycling. When I need to know something, I search online via PubMed or Google Scholar. Topics I want to keep up-to-date at all times have shared searches that update me periodically.

Some journals will now be online-only, either with a fairly traditional publishing model or a more liberal acceptance policy (PLoS One, for example). Platforms such as Figshare allow investigators to make raw data publicly available and citable, even if not included in the final paper for a study. Recently, Beyond the PDF 2 took place in Amsterdam where visionaries gathered to once again discuss the printing press of this century. More information can be found about this conference and conversation here.

PeerJAfter scanning this discussion, I began playing around with PeerJ. The model is intriguing; you pay a lifetime fee up front. You can freely pre-publish works (PeerJ PrePrints) and get public feedback . With a mouse-click, you can send your manuscript to peer review which will be based on scientific soundness of the research without attention to impact or "sex-appeal" factor of the work. The goal here is PLoS One without the high publication fees. For $99 you can become a basic lifetime member, able to submit unlimited public "pre-publications" and publish one peer-reviewed article for life. Of course, you will be expected to also review at least one article for life. All authors on the article must have memberships; if you wait until article acceptance to join, fees will be ~30% greater. Right now, content in PeerJ is limited to biomedical science and health issues. PeerJ only publishes research articles. Literature review articles, commentaries, case reports and other works may instead be submitted to PeerJ PrePrints.

My biggest concern took some digging about the web site:

PeerJ will be indexed in all major Abstracting & Indexing databases, including for example PubMed, PubMedCentral, GoogleScholar, and Microsoft Academic Search. We will also be applying for indexed status in services such as MedLine and Web of Science.

This model certainly has the right price; $99 runs less than the page fees for my last journal submission. As a senior professor, this site may be perfect for some of my less impressive results that I just want to get out there. When I was early in my career, PeerJ would have let me get some new data peer-reviewed and published and still make my grant deadline.

What other new-wave publishing services deserve exploration? Any Whizbangers have experience with PeerJ or similar platforms?

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Interpreting Clinical Studies: Basic Stats

Oct 26 2011 Published by under Evidence Based Medicine, Research issues

Patients demand access to medical research, but often find it an incomprehensible mess. Even after wading through the alphabet soup of abbreviations and clever clinical trial acronyms, what do those numbers mean? Truth be told, many healthcare professionals and medical writers really do not fully appreciate those numbers. That is why an article in the current issues of AMWA Journal provide such a brilliant service:


Click to enlarge

Redfern and Thompson: The risks and hazards of interpreting and reporting health study measures: A simple, practical overview

The authors use some simple examples to define and illustrate the calculation and meaning (see table) of Absolute Risk, Absolute Risk Reduction, Relative Risk, Relative Risk Reduction, Odds Ratio, Hazard Ratio, and Number Needed to Treat. The article is behind a paywall, but I will summarize some of the information here, using my own dataset.

I studied the risk of a kidney defect in mothers with or without an environmental stressor. The control mothers (no stressor) delivered 397 offspring, 48 of which were abnormal. The stressed mothers delivered 316 offspring, 53 of which showed abnormalities.

The Absolute Risk of kidney abnormalities in the control group was 48/397 or 12%. The Absolute Risk in the stressed group was 17%. The Absolute Risk Reduction is the difference in Absolute Risk between the two groups, or, in this case, the 5% increase in risk with the stress. Note that this is merely the difference, not a ratio with anything.

Relative Risk is the probability of an outcome in a "treated" group expressed in relation to the probability of the same outcome in the control group. In my dataset, the risk with stress was (53/316) and the risk in controls (48/397), so the Relative Risk was 1.387 with the stressor. The Relative Risk Reduction (for a treatment that improves outcomes) would be 1-Relative Risk. In this case, the stress increases risk.

As these authors point out, Relative Risk and Relative Risk Reduction are proportional, and the magnitude of Absolute Risk must be kept in mind as well:

A physician may be swayed to initiate a new therapy on the basis of clinical trial results that showed a 50% reduction in outcome compared with standard therapy but may be less impressed if an absolute risk of 2 in 1,000 decreased to 1 in 1,000, even though this also represents a 50% reduction in risk. In general terms, the efficacy of a treatment (in relation to control or another treatment) can be adequately assessed by relative risk reduction, but the absolute risk and the absolute risk difference are needed to provide the context in order to more completely appreciate the effect of a treatment on the population of interest.

The Odds Ratio can be calculated as well to show the odds of an event in an exposed group to that in a control group, so that the ratio is 1 when the odds are identical. The odds of a stressed offspring showing a kidney abnormality would be 53 (number abnormal)/263 (number normal) or 0.20. In my control group, the odds would be 48/349 or 0.14. The Odds Ratio would be the odds for the stressed group divided by the odds for the control group, or 1.465. The Odds Ratio is similar to Relative Risk when the outcome of interest occurs infrequently; however, when the event is fairly common (>10%) then the effect of a variable becomes magnified. In general, Relative Risk is easier to comprehend, but some study designs(such as case-control) will not allow calculation of Relative Risk.

Another useful calculation for clinical material is the Number Needed to Treat, an indirect estimate of risk-benefit. It is calculated as the reciprocal of the Absolute Risk Reduction. For example:

in the Heart Protection Study, a randomized controlled trial with patients at high cardiovascular risk, the absolute risk of all-cause mortality over 5 years was 12.93% (1,328 deaths among 10,269 patients) in the simvastatin group and 14.68% (1,507 deaths among 10,267 patients) in the placebo group over 5 years.19 The absolute risk reduction resulting from exposure to simvastatin is 1.75% (ie, 14.68% – 12.93%). Stated another way, simvastatin reduced the absolute risk of dying by 1.75% (0.0175) over 5 years. The number needed to treat is therefore 57 (ie, 1 ÷ 0.0175). This means that 57 people would need to be treated with simvastatin over a 5-year period to prevent the death of 1 person.

This provides a handy gauge of risk-benefit-cost of a therapy or intervention, but this value must be inextricably linked to the specifics of the given study. In the example above, results can only be assumed for 5 years of treatment. No information can be assumed for other drugs or durations of therapy.

The article includes a nice discussion of Hazard Ratios and Kaplan-Meier curves as well. If you frequently need to discuss the medical literature, particularly clinical trials, this piece provides excellent background on the common statistics.

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Developed with Image Courtesy of PhotoXpress (click for source)

Every few years the folks at the National Institutes of Health (NIH) ask investigators and other interested parties to help define research priorities. These conversations help drive the agenda for extramural funding.

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) is hosting an online dialogue instead of a face-to-face meeting. This virtual event, the Kidney Research National Dialogue (KRND), begins the institute's preparation of  a Blueprint for Kidney Research.

The first phase of KRND runs through March 2011. Participants submit research questions for discussion and voting. Who can participate?

The Division of Kidney, Urologic and Hematologic Diseases (KUH) of the National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) is coordinating this effort in collaboration  professional societies, including the American Society of Nephrology (ASN), American Society of Pediatric Nephrology (ASPN), National Kidney Foundation (NKF), Renal Physicians Association (RPA), and the Polycystic Kidney Disease (PKD) Foundation.  All interested researchers, clinicians and patients are welcome to join the dialogue

Interested parties can request an invitation at or register via the KRND site.

NIDDK wants to identify compelling research questions. How compelling? If answered, the investigator could receive an all-expenses paid trip to Stockholm to pick up a little prize. Yes, that level of compelling. Questions are assigned to broad categories, and the authors tag them with other key words. Participants can comment on any question, making this process into a blog-like asynchronous dialogue (although no PhysioProfisms so far).

The level of conversation becomes important as people vote for their favorites. Each participant receives 20 chips (as in poker, not Doritos) that can be distributed among the questions posed. Chips can be distributed as the participant sees fit. Really like one idea? You can put all 20 there. You can put one on each of 20 different questions, or distribute them anyway in between. Votes help determine which ideas or questions proceed into Phase II.

KRND Landing Page

After Phase I, the voting and discussion should lead to a limited number of broad research areas. Phase II, anticipated for March-April 2011, will focus the discussion on these compelling questions, particularly the strategies to address them. Critical preliminary groundwork will also be identified. Preparation of the Blueprint document in May-June 2011 is Phase III of the process.

First, I want to congratulate Krystyna Rys-Sikora and Robert Star at NIDDK for developing this format. Given the capabilities of the interactive web, this sort of site should work well for this kind of conversation. That said, some in the Nephrology/Urology community have not embraced online interactivity. As of this post, only 1208 users have registered with the site.

If you are reading this post and have any interest in the research NIDDK will fund in the future, your voice should be heard! Click the links and get involved with KRND; if you don't, you have only yourself to blame when NIH ignores your area of interest.

Still need more info? Click for the official KRND Fact Page.

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Dragon Phylogeny

Some people believe that science ignores effective alternative treatments to keep funding research. They really think we would deprive patients of cures to further our livelihoods.

They are wrong.

Some diseases are dragons. With the right sword, they are dead, killed, over. For example, the dragon Polio can be slain by a vaccine. Researchers who had studied the virus' predilection for certain cells in the central nervous system and other characteristics turned to other diseases. Of course, now that we have lived without the horrors of polio for a generation, some people are rejecting the tools that killed the dragon.

Infectious diseases are often dragons. A vaccine, an antibiotic can conquer them. If you miss, though, you may still end up dead. If you conquer them, then you find a new dragon.

Other diseases are more difficult to conquer. We swing our sword and a limb comes off; instead of dying, though, the limb grows back. Or, like some starfish, each piece grows into a new dragon. Or we kill the dragon but injure ourselves in the process.

We keep challenging these complex disorders, these wicked dragons. We try new weapons, sharpen the ones we have, and find new targets. The work is slow and difficult. Herbs and other "alternative" remedies do get studied in our labs. Some work; many do not. If they work they are no longer "alternative" medicine; they are medicine.

Please remember that we want dragons to be extinct. Even if it means early retirement!

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Protection for Clinical Research: The DSMB

Aug 04 2010 Published by under [Medicine&Pharma], Research issues

Ultimately new treatments must undergo testing in people before they can be marketed as new drugs or devices. Testing stuff in people raises all sorts of ethical issues. No matter how many animals have been cured by your next great thing, people may be a bit different and there will be risks, known and unknown. The evolution of these protections can be read, in beautiful moving prose, in The Immortal Life of Henrietta Lacks: internal review boards (IRB), informed consent, and other protections have developed over time since the end of World War II and the revelation of Nazi atrocities and experiments.

Clinical research initially seems pretty simple. Get people, give them a new treatment, and see if they get better. Unfortunately, patients in experiments (or not) may get better spontaneously, especially if their doctors expect it. The placebo effect led to the double-blind clinical trial. Neither the subjects nor the investigators know who is getting the test agent, eliminating a major source of bias in outcomes.

While masking doctors and subjects to study conditions removes bias, it also removes some safety. What if the treatment has an unexpected side effect, especially a deadly one? What if the treatment is more effective than imagined and a significant effect can be demonstrated with only half the original number of subjects? In either of these cases, it would be unethical to continue the trial, but the investigators cannot unmask the data without ruining an ongoing study. As large, multi-center studies became more common in the late 1960's the data safety monitoring board (DSMB) became a common feature of such trials.

Clinical research sandwiched between two layers of supervision

Clinical trials can be the brain-child of an investigator, although many are conceived of by the sponsor, especially in the case of pharmaceutical trials. Large trials frequently involve a steering committee, a group of investigators who devise the study and supervise its performance, analysis, and publication. In general, everyone in the orange boxes in the figure will be masked to subject assignment. If they break the code, then the study must be terminated.

Qualified investigators also compose the DSMB. The committee must include a statistician and physicians with expertise in the disorder under study and potential side effects. The statistician accesses unmasked data periodically and the committee examines the results. Is recruitment going as expected? If patients are stratified for a characteristic, is balance being achieved? Are side effects or mortality occurring in excess in one of the treatment groups? Any of these areas could lead the DSMB to recommend premature termination of the study to the investigators, steering committee, or sponsor. The DSMB also reports to the IRB who can recommend premature termination as well.

A recent article discussed three large clinical trials in which data were unmasked prematurely by the sponsor or investigators, without consulting the DSMB and/or steering committee. I have discussed this article and some of these issues elsewhere.

Bottom line: The DSMB helps protect subjects from a number of outcomes, including undue risks of bad outcomes, missing out on an effective treatment, or being a subject in a trial that ends before the answer is really found.

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