Adherence to Surveillance for Second Malignant Neoplasms and Cardiac Dysfunction in Childhood Cancer Survivors: A Childhood Cancer Survivor Study
Bibliographic record
Abstract
PURPOSE To evaluate childhood cancer survivors’ adherence to surveillance protocols for late effects of treatment and to determine the factors affecting adherence. METHODS Between 2014 and 2016, 11,337 survivors and 2,146 siblings in the Childhood Cancer Survivor Study completed a survey ascertaining adherence to Children’s Oncology Group (COG) guidelines for survivors at high risk for second malignant neoplasms or cardiac dysfunction and to the American Cancer Society (ACS) cancer screening guidelines for average-risk populations. Adherence rates and factors affecting adherence were analyzed. RESULTS Median age at diagnosis was 7 years (range, 0-20.9 years), and median time from diagnosis was 29 years (range, 15-47 years). Among high-risk survivors, adherence to COG breast, colorectal, skin, and cardiac surveillance was 12.6% (95% CI, 10.0% to 15.3%), 37.0% (34.1% to 39.9%), 22.3% (21.2% to 23.4%), and 41.4% (40.1% to 42.7%), respectively. Among average-risk survivors, adherence to ACS breast, cervical, and colorectal screening was 57.1% (53.2% to 61.0%), 83.6% (82.7% to 84.5%), and 68.5% (64.7% to 72.2%), respectively. Twenty-seven percent of survivors and 20.0% of primary care providers (PCPs) had a survivorship care plan (SCP). For high-risk survivors, SCP possession was associated with increased adherence to COG breast (22.3% v. 8.1%; prevalence ratio [PR], 2.52; CI, 1.59 to 4.01), skin (34.8% v 23.0%; PR, 1.16; CI, 1.01 to 1.33), and cardiac (67.0% v 33.1%; PR, 1.73; CI, 1.55 to 1.92) surveillance. For high-risk survivors, PCP possession of a SCP was associated only with increased adherence to COG skin cancer surveillance (36.9% v 23.2%; PR, 1.24; CI, 1.08 to 1.43). CONCLUSION Guideline adherence is suboptimal. Although survivor SCP possession is associated with better adherence, few survivors and PCPs have one. New strategies to improve adherence are needed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".