Meditations of an oncology geek

Archive for September, 2013

On riding and ridding disease, motivations of medical researchers

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27 September 2013

I’ve made another guest appearance in the award-winning science blog Beaker, offering meditations on medical research, health ethos, cycling, and Pedal the Cause.

Image: Jamie Lynch (left) and I recently rode from UCSD to Julian and back, following the inaugural Pedal the Cause route. Not pictured are the copious amounts of Julian Pie consumed shortly thereafter.

There’s a certain duality to medical researchers. On one hand, there’s the immense dedication and time devoted (years, wrinkled skin, and gray hairs) toward the enormously engrossing practice of science. It’s a curious compulsion sharpened by a hunger to discover what has never been known before. I wrote briefly before about this on Beaker a few weeks ago. On the other hand is the deep motivation drawn from compassionate empathy for those crippled by disease. It’s a very human connection, and medical researchers need to allow both forces to guide their inquiry and labor.

Central to this ethos is the assertion that everyone should have the chance to live a happy, productive life. Of course, this ethos extends much further than medical research, and everyone can do a lot to promote healthier, happier living for themselves and those around them, regardless of profession and life circumstances. Medical research marches on and continues to improve lives and grant more birthdays, but the mere absence of disease is not health; medical research is critically important, but it is far from the only initiative toward that end.

Continued here:

Written by Ryon

September 27th, 2013 at 1:06 pm

Posted in Science Blog

Quantifying the Harms of Overdiagnosis?

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17 September 2013

A central tenant of the Hippocratic Oath is “Do No Harm” and a recent article brought to my attention how few clinical trials aimed at early cancer detection measure the harms to patients in the screening process (1). (downloaded for free here:

There is a huge push for early detection in cancer. Groups like the Canary Foundation and the American Cancer Society have early detection squarely in their mission ethos and have aggressively emphasized self-detection and funded research for early detection trials and technologies.

A late 20th century view of cancer progression is that of a long road with distant metastasis (the life-threatening threshold in disease progression) at the end (2), offering a hypothetical window of intervention… if that window was opened by screening. These views are still dominant in many circles, but (at least in the instance of breast cancer) have recently been challenged by a rising tide of clinical trials, epidemiological data, and experimental models of metastasis. Late metastasis is far from universal in solid tumor progression.

Nonetheless, the hypothesis that early detection might lead to a decrease in cancer-associated deaths was rigorously pursued in the last decade, and has resulted in some major changes in screening policy. The culmination of these data resulted in the UK Panel on Breast Cancer Screening recommending a decrease in screening (3). While early stage diagnosis of breast cancer increased with increased early detection measures, the overall reduction in cancer related deaths were so low that it was judged as unethical to screen so many women.

Yesterday, a paper came out in the British Journal of Medicine that took this a step further: the authors attempted to quantify the harms to patients from screening. Harms can come in a variety of forms, and they include (but are not limited to):

-Invasive procedures for early detection (body fluid sampling, biopsies, etc).
-Overdiagnosis (and unnecessary chemical or surgical procedures).
-Unnecessary psychological harm from misdiagnosis of a condition that is not physically harmful.

Results Out of 4590 articles assessed, 198 (57 trials, 10 screening technologies) matched the inclusion criteria. False positive findings were quantified in two of 57 trials (4%, 95% confidence interval 0% to 12%), overdiagnosis in four (7%, 2% to 18%), negative psychosocial consequences in five (9%, 3% to 20%), somatic complications in 11 (19%, 10% to 32%), use of invasive follow-up procedures in 27 (47%, 34% to 61%), all cause mortality in 34 (60%, 46% to 72%), and withdrawals because of adverse effects in one trial (2%, 0% to 11%). The median percentage of space in the results section that reported harms was 12% (interquartile range 2-19%).

Conclusions Cancer screening trials seldom quantify the harms of screening. Of the 57 cancer screening trials examined, the most important harms of screening—overdiagnosis and false positive findings—were quantified in only 7% and 4%, respectively.

If the numbers were not poignant enough, the authors offered a few comments on the matter:

While we acknowledge that collecting data on harms will complicate cancer screening trials, this is not a sound argument against the strong ethical obligation to collect such data. If trialists do not report certain outcomes because they consider that the harms will be either rare or irrelevant when compared with the potential decrease in mortality, such information will not be available for people who judge these outcomes differently. We think that future screening trials should collect and report the expected harms of screening (false positives, overdiagnosis and overtreatment, psychosocial consequences, somatic complications, and all cause mortality). Adequate reporting of harm requires data from the control group as these provide a reference level and help to interpret harms data from the screened group.

Not addressed by the authors is the argument that perhaps increased screening could offer a peace of mind for the concerned. Another recent review article (4) examined the psychological outcomes of patients in response to screening for rare diseases in otherwise healthy patients and found that:

Diagnostic tests for symptoms with a low risk of serious illness do little to reassure patients, decrease their anxiety, or resolve their symptoms…

The take-home message that I get out of this is that we must not assume that any intervention will not be harmful, and that we need to design trials to both quantify this effect and ethically weigh this against data obtained from the results of trials of early detection and beyond. Without such reporting there is no way to know if we are doing more harm than good.


1. Heleno B, Thomsen MF, Rodrigues DS, Jørgensen KJ, Brodersen J. Quantification of harms in cancer screening trials: literature review. BMJ. 2013 2013-09-16 11:34:45;347.
2. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000 Jan 7;100(1):57-70. PubMed PMID: 10647931. Epub 2000/01/27. eng.
3. The benefits and harms of breast cancer screening: an independent review. Lancet. 2012 Nov 17;380(9855):1778-86. PubMed PMID: 23117178. Epub 2012/11/03. eng.
4. Rolfe A, Burton C. Reassurance after diagnostic testing with a low pretest probability of serious disease: systematic review and meta-analysis. JAMA internal medicine. 2013 Mar 25;173(6):407-16. PubMed PMID: 23440131. Epub 2013/02/27. eng.

Written by Ryon

September 17th, 2013 at 11:16 am

Posted in Science Blog

Med Into Grad begins!

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16 September 2013

I’m proud to announce that I’m taking part in the 2013-2014 Med Into Grad Initiative hosted by the UCSD School of Medicine and the Howard Hughes Medical Institute (HHMI).

“Big Data” and “Personalized Medicine” are buzzwords that, to my astonishment and delight, have been born and are currently in their infancy right in front of my own eyes here at the Moores Cancer Center! I’ve spent a fair bit of time studying and applying my knowledge of cancer biology for the sake of cancer biology, but I am very interested in cancer diagnosis and clinical trials. The pace at which new target therapies are entering the clinic is staggering, and it’s truly amazing to see knowledge of signaling pathways and phenomena being utilized that a decade ago might have been regarded as esoteric to the point of banality for lack of tools of clinical intervention.

This week my 12 classmates and I began our coursework in anticipation of spending January through March 2014 away from the lab bench and in the clinic. And for me, “clinic” entails inpatient and outpatient oncology clinics, med school classes, tumor boards, and grand rounds. I’ll be shadowing oncologists and observing the nuts and bolts of current cancer therapy.

Although I’ve been attending tumor boards here at the Moores Cancer Center for some time now, Med Into Grad will allow me a new level of access to the broader knowledge (perspective) base that I seek to participate in this emerging age of oncology and medicine.


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Written by Ryon

September 14th, 2013 at 7:37 pm

Posted in Science Blog

The Future was Yesterday at the 25th Usha Mahajani Symposium on Cancer Genomics at the Salk Institute

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10 September 2013

Yesterday I had the pleasure of attending the 25th Usha Mahajani Symposium at the Salk Institute. This year’s theme was Cancer Genomics, an extremely hot area of research right now. It attracted an all-star cast of international bioinformaticians with “TED-quality” presentations, as referred to by a colleague.

Kenna Shaw is the (now-former) director of The Cancer Genome Atlas project (I’ve often wondered if the acronym TCGA was not perhaps a tad too perfect) and gave a great talk on the progress of the database and some of the fundamental insights into cancer biology already discovered in the process. They are approaching their goal of 500 cancer genomes per cancer type* with matching mRNA, copy number variation, survival data and more for both tumor tissue and matching normal tissue (usually blood). My favorite browser for this data is the cBioPortal from Sloan-Kettering.

*I find it somewhat ironic that TCGA data is organized by gross histological subtype – using a system of organization that it is simultaneously making obsolete.

It was not originally clear to me that only malignant tumor cases are represented. None of the patients had carcinomas in situ. Also, all of the patients were treatment-naiive. The data has not been affected by selection pressures of chemotherapy.

One of the best messages put forth by Shaw in her dense, frenetic paced talk was the need to look not just at genomic data, but all of the -omics, and the lengths her groups went through to get complete data on many fronts for these cancer patient samples.

Rene Bernards gave a fantastic talk outlining a resistance mechanism to vemurafenib, a BRAF V600E inhibitor that became available for melanoma a few years ago. In what seemed very odd at first, the upstream kinase EGFR was upregulated to escape BRAF / MEF / ERK blockade, which lead to PI3K pathway activation. The takeaway messages from his talk were twofold for me:

1) Cellular circuitry is much more redundant than we intuitively think and we’ve likely just begun to uncover many of the resistance pathways to targeted chemotherapy.
2) Understanding these most common resistance pathways might allow complementary blockade through combinational therapy (a PI3K or mTOR inhibitor paired with vemurafenib, for instance).

Atul Butte produced a vision of what computational biological labs (and garage biotech startups) might look like in the future. He stressed the point that it’s becoming more and more possible to “outsource everything but the questions.” He then told a story of his own research projects that was more about the process than the result, namely the use of several powerful pharmaceutical research experiment vendors like Assay Depot combined with (shockingly free) resources like the massive genome array database Gene Expression Omnibus and Chem Pub, and when topped off with the (yes, free) central clinical trials database IMMPort. Butte produces a vision (business model?) for someone with the appropriate computational skillset to create an academic research lab (or garage biotech company) with minimal overhead.

Razelle Kurzrock‘s presentation is worthy of its own follow-up article and commentary. She stressed that we absolutely need to change the way we conduct early stage clinical trials for targeted therapies. Toward that end, a few main messages from her talk:

1) We are shooting ourselves in the foot trying out new targeted therapies in patients that are already refractory for disease. She made many parallels to the CML / Imatinib revolution that resulted from treating early-stage patients with BCR-ABL blockade.

2) We need to organize clinical trials around “molecular hubs” (i.e. the EGFR / RAF / MEK / ERK / PI3K / mTOR axis) not necessarily tumor-tissue-of-origin type, and validate molecular hub targeting strategies, not specific drugs.

3) We need to determine rules of thumb for safe drug combinations, since the specific tailored combinations received by patients in her vision might might be rare and not vetted by thousands of patients getting the same tailored combinations.

Overall I had a great time at the symposium and look forward to attending next year.


Written by Ryon

September 10th, 2013 at 1:39 pm

Posted in Science Blog

All the kids are above average…

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6 September 2013

Didactic cognitive bias education could be very useful for medical researchers (and would have saved me a lot of head-banging!)

Image: Colloquially referred to as the “Lake Wobegon Effect” the experimentally derived Dunning-Krueger Effect explains why humans frequently believe they are more proficient at things than they actually are.

This morning I read a brilliant essay on the neuroscience of perception to discuss how internal biases develop by Robert Burton in Nautilus Magazine, Issue 5

Asking a juror to be ‘objective,’ recognize and control innate biases and understand his or her lines of reasoning, flies in the face of the evolving science of decision-making. The harsh and scary reality is the scales of justice aren’t tipped in the open courtroom; the real action occurs out of sight.

A few years back I started to understand the power that ubiquitous cognitive biases have in perception and decision-making. Likewise, I began to actively seek consciousness of innate biases, much like one would take up a workout routine or a new hobby. It’s an ongoing process, but as time goes on I’ve gotten much better recognizing my own biases of logic and reasoning, but also those of friends, colleagues, collaborators, and those published in the scientific literature.

Recognition is one thing, but countering intuition takes practice and persistence. Why do I “know” it’s not going to rain today? How and why do we overlook the obvious? Does a fish know it’s in water? What if this model of cancer metastasis is an association fallacy of a celebrity scientist bolstered by the momentum of hundreds of non-questioning researchers over time?

With my graduation less than a year away I’m frequently asked things like “what are you going to do with your PhD?” or “what will it allow you to do?” I’ll be the doctor that can’t help anyone! But really, one of the most valuable skills I’ve gained is how to recognize how cognitive biases affect my work (and every day life). From how I design my experimental controls, why I chose certain thresholds, what statistics would be most appropriate, to what I eat for breakfast and why I insist on riding my bike instead of driving when there’s a 50% chance of rain (that weatherman’s just a talking head, right?) I’ve come to recognize how pervasively influential innate cognitive biases are in everything I do, and how invaluable understanding these processes are for young scientists.

Toward that end, I’d like to think out loud that perhaps didactic training (i.e. classes) in cognitive biases would be very beneficial for PhD students. After all, the PhD is not about learning what to think, but how to think.

Admittedly I’m not very well versed in the coursework of many PhD programs, but I’ve never heard of formal training to recognize cognitive biases as a means to produce better scientists. Perhaps this is commonplace in some circles? Or maybe my circle is the odd exclusion? Maybe this is something the better scientists learn on their own without realizing it? These mind-twisters burn like 50-pound single arm curls for my brain, but I’m always glad I did the workout!


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Written by Ryon

September 6th, 2013 at 4:40 pm

Posted in Science Blog

Health Insurance vs. Health Assurance: Part 1

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2 September 2013

The reason why I do cancer research (and perhaps why we as a society subsidize medical research) is because we believe that everyone deserves the chance to live the happiest, most meaningful, productive life as possible. While I’ll be the first to admit the absence of disease is not health, there is no denying that it’s much easier to attain life goals without the burden of disease, be it cancer, diabetes, or obesity.

In the lab I fight cancer with some pretty high-tech means. Outside of the lab I do so in more subtle ways. One of these ways is commuting to work via bicycle. Unless it’s torrential rain (rare here in southern California) I will ride my bike to work. I also ride my bike to get groceries. And to the dry cleaners. And to social events. And to meetings with collaborators. The list goes on, I want to stress that the bike is my primary mode of transportation despite owning a truck. Part of the reason why I do so is economic: the annual operating cost of a bicycle is about $300 (Moritz, 1997). In my own experience, it’s been even less than that for my commuter bike. There is also a growing body of evidence to suggest that aerobic exercise (like commuting via bicycle) is a very effective means to reduce cancer risk on many fronts. In fact, I will risk going out on a limb here and declare that it’s some of the best data I’ve seen for broad-spectrum cancer prevention.

In the near future I will re-visit the relationship between exercise and cancers (It’s been a few years and there’s new data), but I would first like to share a brilliant TED talk about the benefits of cycling by Dr. Allen Lim.

Below are a few points from his talk that deserve re-iterating.

From having spent the better part of the last decade working on a cure, it is my opinion that the best defense remains a good offense: prevention. At the current time one cannot buy insurance from cancer. There is no magic bullet (pill), no magic diet, no special sauce. In future articles I will present information on how I came to discover perhaps the most effective anti-cancer device I know: the bicycle. This first article (and Lim’s talk) merely scratches the surface of some of the other benefits of this incredible device.


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Written by Ryon

September 2nd, 2013 at 2:46 pm

Posted in Science Blog