A seemingly slight adjustment in a statistic, for teaching purposes, can significantly change a test’s calculated value….
She writes: “I believe that every educated person must at the very least understand how these interpreters of medical knowledge examine, or should examine, it to arrive at the conclusions.”
What’s clear is that depending on how investigators adjust or manipulate or clarify or frame or present data – you choose the verb – they might show differing results. This doesn’t just pertain to data on trauma and helicopters…
The new findings have no bearing on whether or not cancer screening is cost-effective or life-saving. What the study does suggest is that med school math requirements should be upped and rigorous, counter to the trend
Last week I came upon a new term in the cancer literature: the Disease Control Rate. The DCR refers to the total proportion of patients who demonstrate a response to treatment. In oncology terms: The DCR is the sum of complete responses (CR) + partial responses (PR) + stable disease (SD). Another way of explaining […]
Earlier this month, the ACS released its annual report on Cancer Facts and Figures. The document, based largely on analyses of SEER data from the NCI, supports that approximately 229,000 adults in the U.S. will receive a diagnosis of invasive breast cancer (BC) this year. The disease affects just over 2,000 men annually; 99% of […]
In his latest New Yorker piece The Truth Wears Off, Jonah Lehrer directs our attention to the lack of reproducibility of results in scientific research. The problem is pervasive, he says: …now all sorts of well-established, multiply confirmed finding have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims […]
ML learned a new word upon reading the newspaper: floccinaucinihilipilificationism. According to the New York Times now, Moynihan prided himself on coining the 32-letter mouthful, by which he meant “the futility of making estimates on the accuracy of public data.”
She’s not exactly sure how the term, said to be the longest non-technical word in the English language, might be used in medical communication, but it seems that it might be relevant to estimating health care costs, and – possibly by extrapolation – to understanding the hidden ambiguousness of inferences drawn from vast amounts of seemingly hard data.
A Small Study Offers Insight On Breast Cancer Patients’ Capacity and Eagerness to Participate in Medical Decisions
Last week the journal Cancer published a small but noteworthy report on women’s experiences with a relatively new breast cancer decision tool called Oncotype DX. This lab-based technology, which has not received FDA approval, takes a piece of a woman’s tumor and, by measuring expression of 21 genes within, estimates the likelihood, or risk, that her tumor will recur.
As things stand, women who receive a breast cancer diagnosis face difficult decisions…
Why bother, you might ask – wouldn’t it be easier to drop the subject?
“Make it go away,” sang Sheryl Crow on her radiation sessions.
I’ll answer as might a physician and board-certified oncologist who happens to be a BC survivor in her 40s: we need establish how often false positives lead, in current practice, to additional procedures and inappropriate treatment…These numbers matter. They’re essential to the claim that the risks of breast cancer screening outweigh the benefits.