Question

In an article in the Archives of Your Specialty, researchers report that screening Test T is enormously effective, and should be used routinely. As evidence, they report that the five-year survival rate of patientsS whose disease was discovered by screening with Test T is 90%, whereas the five-year survival rate of patients whose disease was discovered by other means is only 60%. However, in an article that same month in the Journal of the College of Your Specialty, another group of researchers report that screening with Test T has no effect. As evidence, they report that a study which randomized subjects to a program of routine screening with Test T or to no special screening regimen found an 80% five-year survival rate in both groups. The issue seems even more confusing because this second group of investigators acknowledges that if their data are reanalysed to compare the survival rate of subjects who actually followed the screening regimen to those who did not, whatever group they were assigned to, the cohort of those who actually were screened had five year survival of 85% whereas the cohort of those who were not had survival of only 75%. Despite this, these investigators maintain the position that no effect of screening has been demonstrated. Write a brief note for the General Practitioner's Quick Office Practice Digest, explaining why these various sets of results might be expected to in the way they do and advising whether or not to screen with Test T

Answer 1

The causes of statistical illiteracy should not be attributed to cognitive biases alone, but to the emotional nature of the doctor–patient relationship and conflicts of interest in the healthcare system. The classic doctor–patient relation is based on (the physician's) paternalism and (the patient's) trust in authority, which make statistical literacy seem unnecessary; so does the traditional combination of determinism (physicians who seek causes, not chances) and the illusion of certainty (patients who seek certainty when there is none). We show that information pamphlets, Web sites, leaflets distributed to doctors by the pharmaceutical industry, and even medical journals often report evidence in nontransparent forms that suggest big benefits of featured interventions and small harms. Without understanding the numbers involved, the public is susceptible to political and commercial manipulation of their anxieties and hopes, which undermines the goals of informed consent and shared decision making.

the importance of teaching statistical thinking and transparent representations in primary and secondary education as well as in medical school. Yet this requires familiarizing children early on with the concept of probability and teaching statistical literacy as the art of solving real-world problems rather than applying formulas to toy problems about coins and dice. A major precondition for statistical literacy is transparent risk communication. We recommend using frequency statements instead of single-event probabilities, absolute risks instead of relative risks, mortality rates instead of survival rates, and natural frequencies instead of conditional probabilities. Psychological research on transparent visual and numerical forms of risk communication, as well as training of physicians in their use, is called for.

Statistical literacy is a necessary precondition for an educated citizenship in a technological democracy. Understanding risks and asking critical questions can also shape the emotional climate in a society so that hopes and anxieties are no longer as easily manipulated from outside and citizens can develop a better-informed and more relaxed attitude toward their health.

Therefore, in the first study there was lead time bias, length/time bias, and compliance bias. In the second study, when they originally did the randomized clinical trial those biases were gone due to randomization, but when they (non-randomly) re-grouped within the randomized groups the biases came back. The screening therefore does not seem to help.