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We make decisions based on the data we see. One restaurant serves higher-quality food than another. One presidential candidate aligns more appropriately with our values. One surgical technique yields better outcomes. One applicant submits a stronger job application than a competitor. From these data, we decide what course of action to take. In many cases, these decisions are inconsequential. In others, however, a poor decision may lead to dangerous results. Let’s consider danger.

Imagine you are a surgeon. A patient arrives in your clinic with a particular condition. Let us call this condition, for illustrative purposes, phantasticolithiasis. The patient is in an immense amount of pain. After reviewing the literature on phantasticolithiasis, you discover that this condition can be fatal if left untreated. The review also describes two surgical techniques, which we shall call “A” and “B” here. Procedure A, according to the review, has a 69% success rate. Procedure B, however, seems much more promising, having a success rate of 81%. Based on these data, you prepare for Procedure B. You tell the patient the procedure you will be performing and share some of the information you learned. You tell a few colleagues about your plan. On the eve of the procedure, you call your old friend, a fellow surgeon practicing on another continent. You tell him about this interesting disease, phantasticolithiasis, what you learned about it, and your assessment and plan. There is a pause on the other end of the line. “What is the mass of the lesion?” he asks. You respond that it is much smaller than average. “Did you already perform the procedure?” he continues. You tell him that you didn’t and that the procedure is tomorrow morning.

“Switch to procedure A.”

Confused, you ask your friend why this could be true. He explains the review a bit further. The two procedures were performed on various categories of phantasticolithiasis. However, what the review failed to mention was that procedure A was more commonly performed on the largest lesions, and procedure B on the smallest lesions. Larger lesions, as you might imagine, have a much lower success rate than their smaller counterparts. If you separate the patient population into two categories for the large and small lesions, the results change dramatically. In the large-lesion category, procedure A has a success rate of 63% (250/400) and procedure B has a success rate of 57% (40/70). For the small lesions, procedure A is 99% successful (88/89) and procedure B is 88% successful (210/240). In other words, when controlling for the category of condition, procedure A is always more successful than procedure B. You follow your friend’s advice. The patient’s surgery is a success, and you remain dumbfounded.

What’s happening here is something called Simpson’s paradox. The idea is simple: When two variables are considered (for example, two procedures), one association results (procedure B is more successful). However, upon the conditioning of a third variable (lesion size), the association reverses (procedure A is more successful). This phenomenon has far-reaching implications. For example, since 2000, the median US wage has increased by 1% when adjusted for inflation, a statistic many politicians like to boast about. However, within every educational subgroup, the median wage has decreased. The same can be said for the gender pay gap. Barack Obama in both of his campaigns fought against the gap, reminding us that women only make 77 cents for every dollar a man earns. However, the problem is more than just a paycheck, and the differences change and may even disappear if you control for job sector or level of education. In other words, policy change to reduce the gap need to be more nuanced than a campaign snippet. A particularly famous case of the paradox arose at UC Berkeley. In this case, the school was sued for gender bias. The school admitted 44% of their male applicants and only 35% of their female applicants. However, upon conditioning for each department, it was found that women applied more often to those departments with lower rates of admission. In 2/3 of the departments, women had a higher entrance rate than men.

The paradox seems simple. When analyzing data and making a decision, simply control for other variables and the correct answer will emerge. Right? Not exactly. How do you know which variables should be controlled? In the case of phantasticolithiasis, how would you know to control for lesion size? Why couldn’t you just as easily control for the patient’s age or comorbidities? Could you control for all of them? If you do see the paradox emerge, what decision should you then make? Is the correct answer that of the conditioned data or that of the raw data? The paradox becomes complicated once again.

Judea Pearl wrote an excellent description of the problem and proposed a solution to the above questions. He cites the use of “do-calculus,” a technique rooted in the study of Bayesian networks. Put more simply, his methods find causality between a number of variables. In doing so, one can find the conditioning variables and can then decide whether the conditioned data or the raw data are best for decision-making. The set of variables that dictate causality are the ones that should be used. If you are interested in the technique and have some experience with the notation, I recommend this brief review on arXiv.

Of course, rapid and rather inconsequential decisions need not be based on such formalities. On the other hand, it serves all of us well if we at least consider the possibility of Simpson’s paradox on a day-to-day basis. Be skeptical when reading the paper, speaking with colleagues, and making decisions. Finally, if you’re ever lucky enough to be the first patient with phantasticolithiasis, opt for procedure A.

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A Troubling Divorce

March 23, 2013 — Leave a comment

The unhappy marriage between the United States government and science (research, education, outreach) ended this month. We’ve known for years now that the relationship was doomed to fail, with shouting matches in Washington and fingers pointed in all directions. I would more likely describe an end to the relationship between elected officials and human reason, but that would be harsh, and I still have hope for that one. Sadly, this generation of congresspeople signed the paperwork for a divorce with science.

America’s love affair with science dates back to its origins. Later, Samuel Slater’s factory system fueled the Industrial Revolution. Thomas Edison combatted with Nikola Tesla in the War of the Currents. It was a happy marriage, yielding many offspring. The Hygienic Laboratory of 1887 grew into the National Institutes of Health approximately 50 years later. We, the people, invented, explored, and looked to the stars. Combined with a heavy dose of Sputnik-envy, Eisenhower formed the National Aeronautics and Space Administration (NASA) in July 1958. We, the people, then used our inventions to explore the stars.

Since then, generations of both adults and children have benefited from the biomedical studies at the NIH, the basic science and education at the NSF, and the inspiration and outreach from NASA. Since Goddard’s first flight through Curiosity’s landing on Mars, citizens of the United States have not only directly benefited from spin-offsbut also through NASA’s dedication to increasing STEM (science, technology, engineering, mathematics) field participation. Informed readers will know that although the STEM crisis may be exaggerated, these fields create jobs, assuming benefits from manufacturing and related careers. Such job multipliers should be seen as beacons of hope in troubling times.

Focusing on the NIH, it should be obvious to readers that biomedical science begets health benefits. From Crawford Long’s (unpublished and thus uncredited) first use of ether in the 18th century through great projects like the Human Genome Project, Americans have succeeded in this realm. However, as many know, holding a career in academia is challenging. Two issues compound the problem. First, principal investigators must “publish or perish.” Similar to a consulting firm where you must be promoted or be fired (“up or out”), researchers must continue to publish their results on a regular basis, preferably in high-impact journals, or risk lack of tenure. The second problem lies in funding. Scientists must apply for grants and, in the case of biomedical researchers, these typically come from the NIH. With funding cuts occurring throughout the previous years, research grants (R01) have been reduced both in compensation per award and number awarded. Additionally, training grants (F’s) and early career awards (K’s) have been reduced. Money begets money, and reduction in these training and early career grants make it even more difficult to compete with veterans when applying for research grants. Thus, entry into the career pathway becomes ever the more difficult, approaching an era where academia may be an “alternative career” for PhD graduates.

The United States loved science. The government bragged about it. We shared our results with the world. Earthriseone of my favorite images from NASA, showed a world without borders. The astronauts of Apollo 8 returned to a new world after their mission in 1968. This image, the one of the Earth without borders, influenced how we think about this planet. The environmental movement began. As Robert Poole put it, “it is possible to see that Earthrise marked the tipping point, the moment when the sense of the space age flipped from what it meant for space to what it means for Earth.” It is no coincidence that the Environmental Protection Agency was established two years later. A movement that began with human curiosity raged onward.

Recently, however, the marriage between our government and its science and education programs began to sour. Funding was cut across the board through multiple bills. Under our current administration, NASA’s budget was reduced to less than 0.5% of the federal budget, before the cuts I am about to describe. The NIH has been challenged too, providing fewer and fewer grants to researchers, forcing many away from the bench and into new careers. Funding for science education and outreach subsequently fell, too. Luckily, other foundations, such as the Howard Hughes Medical Institute, picked up part of the bill.

I ran into this problem when applying for a grant through the National Institutes of Health and discussing the process with my colleagues. I should note as a disclaimer that I was lucky enough to have received an award, but that luck is independent of the reality we as scientists must face. The process is simple. Each NIH grant application is scored, and a committee determines which grants are funded based upon that score and funds available. With less money coming in, fewer grants are awarded. Thus, with cuts over the past decade, grant success rates plummeted from ~30% to 18% in 2011. When Congress decided to cut its ties with reality in March and allow for the sequester, it was estimated that this number will drop even further. (It should be noted that a drop in success rate could also be due to an increase in the number of applications, and a large part of that decrease in success rate over 10 years was due to the 8% rise in applications received.) This lack of funding creates barriers. Our government preaches that STEM fields are the future of this country, yet everything they have done in recent history has countered this notion. As an applicant for a training grant, I found myself in a position where very few grants may be awarded, and some colleagues went unfunded due to recent funding cuts. This was troubling for all of us, and I am appalled at the contradiction between rhetoric in Washington and their annual budget.

Back to NASA. As we know, President Obama was never a fan of the organization when writing his budget, yet he spoke highly of the agency when NASA succeeded. Cuts proposed by both the White House and Congress to NASA in 2011 for a reduction of $1.2 trillion over 10 years have already been in place. This was enough to shut down many programs, reduced the number employed, and led to the ruin of many of its buildings. However, the sequester, an across-the-board cut, also hit NASA very hard. As of yesterday, all science education and outreach programs were suspended. This was the moment that Congress divorced Science.

All agencies are hit hard by these issues, and it isn’t just fields in science, education, and outreach. Yet, speaking firsthand, I can say that these cuts are directly affecting those of us on the front line, trying to enter the field and attempting to pursue STEM-related careers. Barriers are rising as the result of a dilapidated system. Having had numerous encounters with failed F, K, and R awards amongst friends and colleagues simply due to budget constraints (meaning that their score would have been awarded in a previous year, but the payline was lowered to fund fewer applications) and seeing children around New York who are captivated by science education but are within a system without the funds to fuel them, I can comfortably claim that we are all the forgotten children of a failed marriage.

Whether it be due to issues raised in this post or your own related to the sequester, remember that this is a bipartisan issue. There are no winners in this game, except for those congresspeople whose paychecks went unaffected after the sequester. I urge you to contact your elected official. Perhaps, we can rekindle this relationship.

Recently, the Lancet posted yet another article on Obama’s Global Health Initiative. In it, the writer points out the numerous failures of the GHI. The $63 billion budget was not new money and was instead a new label for funds already budgeted elsewhere. Where GHI differed was in its goal to place all of the leadership under one organization. A central office was created, but this was shut down in July. The article then focuses its text on the tensions that arose when USAID took over as the leaders of the program. I could go on about the successes and failures of the global health initiatives, but I would prefer to focus on a more important issue. What are the GHIs? It is my belief that productive debate will arise if and only if we are adequately informed.

The Global Health Initiatives focus mainly on infectious disease and strengthening healthcare systems around the world. Prior to the Obama administration, they were many organizations (and if we are to be honest, still act as such). PEPFAR and the Global Fund to Fight AIDS focused on HIV/AIDS. The Global Fund also targeted tuberculosis and malaria. The GAVI Alliance put its efforts into immunization. The World Bank’s MAP dealt with AIDS and nutrition. These are not foci of the United States, and Obama’s plan called for a comprehensive effort similar to (and including) these programs that would combine their efforts to improve their effectiveness.

I will instead focus on the current administration’s global health initiative, without a critique. In November 2009, the goal of the GHI was to double US aid for global health to approximately $16 billion per year in 2011, establish goals for the US to assist in addressing the Millennium Development Goals, and attempt to scale up domestic health efforts. The six areas of focus included HIV, tuberculosis, malaria, reproductive health, health systems, and neglected tropical diseases. The November report made three recommendations. First, the group wished to define measurable GHI targets. These would be US-specific and would focus on the delivery of care. Second, they recommended funding be increased to $95 billion over six years, an increase from the original budget. Finally, the recommended that the GHI focus on outcomes and be people-based. Overall, the recommendations were subtle and not clearly defined, but they hinted at the theme of the GHI. The goal was to provide a comprehensive program in which the United States could better address global health initiatives. This was sold as change from the disease-specific nature of Bush’s programs to one that focused on health systems and delivery.

In July 2012, the GHI office was officially closed by the Obama administration. It was touted as a productive shift, but the reality was that this closure was due to myriad problems encountered by the program. The program lacked core leadership, and those in the developing world had troubles with knowing what defined a GHI project. While it had a huge budget, there were only four full-time employees in the office. The idea remained, but the office did not.

There is far more to this story, but that is what you should know about Obama’s GHI. It was and still is an interesting idea, but it remained an idea. What we need are solutions with better focus.