Agreement of medical record abstraction and self‐report of breast cancer treatment with an extended recall window
Bibliographic record
Abstract
Abstract Background Medical record abstraction (MRA) and self‐report questionnaires are two methods frequently used to ascertain cancer treatment information. Prior studies have shown excellent agreement between MRA and self‐report, but it is unknown how a recall window longer than 3 years may affect this agreement. Methods The Women’s Environmental Cancer and Radiation Epidemiology (WECARE) Study is a multicenter, population‐based case‐control study of controls with unilateral breast cancer individually matched to cases with contralateral breast cancer. Participants who were diagnosed with a first primary breast cancer from 1985 to 2008 before the age of 55 years completed a questionnaire that included questions on treatment. First primary breast cancer treatment information was abstracted from the medical record from radiation oncology clinic notes for radiation treatment and from systemic adjuvant treatment reports for hormone therapy and chemotherapy. Agreement between MRA and self‐reported treatment was assessed with the kappa statistic and corresponding 95% confidence intervals (CIs). Results A total of 2808 participants with MRA and self‐reported chemotherapy treatment information, 2733 participants with MRA and self‐reported hormone therapy information, and 2905 participants with MRA and self‐reported radiation treatment information were identified. The median recall window was 12.5 years (range, 2.8–22.2 years). MRA and self‐reported treatment agreement was excellent across treatment modalities (kappachemo, 98.5; 95% CI, 97.9–99.2; kappahorm, 87.7; 95% CI, 85.9–89.5; kapparad, 97.9; 95% CI, 97.0–98.7). There was no heterogeneity across recall windows (pchemo = .46; phorm = .40; prad = .61). Conclusions Agreement between self‐reported and MRA primary breast cancer treatment modality information was excellent for young women diagnosed with breast cancer and was maintained even among women whose recall window was more than 20 years after diagnosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.090 | 0.213 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".