Bibliographic record
Abstract
Strictly speaking, Inova Fairfax Hospital in Fairfax, VA is “outside the Beltway,” but irrespective of its Zip code, Fairfax is an “inside the beltway” type of place where most of the patients are on Uncle Sam's payroll and many of the physicians know the ins-and-outs of Congressional testimony and government funding. It's where Steven H. Woolf, MD, MPH, a member of the United States Preventive Services Task Force (USPSTF), is a professor of family and preventive medicine and it's a setting that makes him acutely aware of political pressure—a sixth sense that he used in explaining the Task Force's new mammography screening recommendations. The USPSTF's recommendation that women undergo screening mammography every one to two years beginning at age 40 has been both cheered and jeered since it was released earlier this year. When the Task Force published the full article last month in Annals of Internal Medicine (2002;137:, 344–346;347–360), the debate only intensified. To be fair, the continuing controversy is hardly surprising, since Annals published those papers in a package that included two editorials that questioned the basis for the recommendation and the latest analysis of follow-up data from the Canadian National Breast Screening Study-1 (CNBSS-1), which still found no benefit for mammography screening for women in their 40s. Right Recommendations But Dr. Woolf, who coauthored the USPSTF papers, remains steadfast in his contention that the group made the right recommendations, at the right time, and for the right reasons. And politics, he said, had nothing to do with it. Both critics and supporters of the recommendations told OT that they believed that the Task Force was pressured into recommending mammography screening for younger women. Not so, said Dr. Woolf. “I am very conscious of this concern…over the years I have seen national guidelines influenced by political pressure. This was not one of them.” He said that some aspects of the guidelines make them an easy target for charges of political influence, and he noted that even the announcement of the new recommendations by Health and Humans Services Secretary Tommy Thompson could be construed as political. Moreover, Dr. Woolf said he did know that in 1997 Congress did pressure the “National Cancer Institute to change its guidelines, and it [Congress] did raise budget issues as part of that pressure. That has been documented.” Yet, Dr. Woolf maintained that it was different this time. While he said that it is possible that “there may have been pressure on the agency, it didn't get down to the level of influencing what we did [as USPSTF members].” The Task Force is part of the Agency for Healthcare Research and Quality. He said the only issue on the table during deliberations was evidence. And the evidence came from pooled data from randomized controlled trials of mammography. “The Canadian study was the only one that was negative,” he said. Critics Unconvinced Anthony B. Miller, MB, FRCP, however, the lead investigator of the Canadian study, remains openly critical of the USPSTF recommendations. Dr. Miller, who is a consultant to the World Health Organization and head of the division of clinical epidemiology at the German National Cancer Institute, said the latest findings from the CNBSS-1 include 16 years of follow-up that “confirm no survival benefit for mammography screening in younger women.” The latest CNBSS-1 report, which was also published in Annals (2002;137:, 305–312), found 105 breast cancer deaths among women who had annual mammography and 108 breast cancer deaths among women who were followed with usual care, meaning clinical breast examinations and mammography when a suspicious lump was detected. Thus, Dr. Miller contends that there is no evidence that screening mammography can reduce mortality by 20% or more, which he regards as a threshold to prove that mammography is beneficial. Steven N. Goodman, MD, MHS, PhD, an epidemiologist at the Kimmel Cancer Center of Johns Hopkins University, said that there might be harm associated with mammography. Specifically, Dr. Goodman said that “mammography is associated with excess surgery. I don't mean just excess biopsies but an actually excess number of lumpectomies and mastectomies.” Dr. Goodman wrote one of two editorials that were published along with the USPSTF guidelines and the Canadian study results. Aside from the well-known risks of false positives and false negatives, he said that mammography is associated with a high rate of excess surgery—both lumpectomy and mastectomy. The problem, he said, is that mammography often detects DCIS that probably requires no surgical treatment but when it is detected by mammography “surgery will follow.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".