Bibliographic record
Abstract
FigureBOSTON—The first session of the Quality Care Symposium, held here last month, was devoted to presentations on overtreatment in cancer care, and the main takeaway is that oncologists recognize overtreatment is rampant but they don't know what to do about it. Lisa Hicks, MD, from St. Michael's Hospital at the University of Ontario, listed several factors that promote overutilization, including a medical culture that says that more tests and treatments are better; defensive medicine; financial incentives to do more; the rapid change in science; a patient culture that every problem can be solved; and direct-to-consumer marketing. The idea behind the American Board of Internal Medicine Foundation's “Choosing Wisely” campaign is to give physicians and patients straightforward ideas about how to avoid inappropriate utilization. So are oncologists using the “Choosing Wisely” advice? Some are, some aren't, according to the results of a study showing that overall adherence to ASCO's initial Top 5 list, issued in 2012, of things that oncologists and their patients should question before proceeding, varied from 51 to 78 percent (Abstract 178). Karma Kreizenbeck, Project Director at Hutchinson Institute for Cancer Outcomes Research at Fred Hutchinson Cancer Research Center, presented the study, which used a database that linked the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) records for about 24,000 cancer patients diagnosed in western Washington state between 2007 and 2013 with enrollment and claims data from Premera Blue Cross. The initial Top 5 items were as follows: No anticancer therapy for patients with advanced cancer and poor performance status; No PET, CT, and bone scans in early prostate cancer; No PET, CT, or radionuclide bone scans in early breast cancer; No biomarkers or advanced imaging following breast cancer treated for cure; and No colony-stimulating factors for chemotherapy with less than a 20 percent risk for febrile neutropenia. Kreizenbeck and her colleagues found: 59 percent adherence to the measure “no chemotherapy or radiation for solid tumors in the last two months of life” for patients with advanced disease; 79 percent adherence to the measure “no PET, CT, and bone scans within two months of early prostate cancer diagnosis”; 97 percent adherence to the measure “no PET, CT, and bone scans within two months of early breast cancer” for patients with tumors in situ; 57 percent adherence to the measure “no PET, CT, bone scans, and tumor markers between two and 14 months after curative therapy for early breast cancer” for patients with localized tumors; and 83 percent compliance to the measure “no colony-stimulating factors with 45 days of chemotherapy start for patients with breast, non-small-cell lung cancer and colorectal cancer who have less than a 20 percent risk for febrile neutropenia.”
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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 0.014 |
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".