Underdiagnosis and undertreament of modifiable cardiovascular risk factors: A Childhood Cancer Survivor Study (CCSS) report.
Bibliographic record
Abstract
10515 Background: Survivors of childhood cancer exposed to cardiotoxic therapies are at increased risk of heart disease. Hypertension, dyslipidemia, and diabetes are modifiable cardiovascular risk factors (CVRFs) that synergistically increase this risk. Therefore, we aimed to determine the prevalence of and predictors associated with CVRF underdiagnosis and undertreatment in this population. Methods: CCSS participants at increased risk of heart disease due to prior cancer therapy were enrolled in an ongoing randomized intervention trial (NCT03104543) to improve CVRF identification and treatment. Participants completed a baseline survey (CVRF status, lifestyle habits, attitudes towards healthcare), anthropometry, and blood draw. Blood pressure, low density lipoprotein, triglyceride, glucose and Hgb A1c were measured and classified as normal/abnormal per standard clinical criteria. Multivariable logistic regression estimated odds ratios (OR [95% confidence intervals]) associated with predictors and risk of CVRF underdiagnosis and undertreatment. Results: As of January 2020, 522 participants (43% male) were available for analysis (47% response), with a median age 38y (range 20-65) and 28y (18-49) from original cancer treatment (75% anthracycline, 47% chest radiation). With mean measured BMI 27.3±6.5 kg/m2, self-reported prevalence rates were hypertension 27%, dyslipidemia 33%, and diabetes 9%. While 90% of participants had a routine check-up ≤2y ago, 58% had a measured CVRF in the abnormal range. Specifically, among previously undiagnosed participants, we observed rates of abnormal blood pressure (26%), lipids (17%), and glucose tolerance (27%). Among those with pre-existing hypertension, dyslipidemia, and diabetes, 11%, 49%, and 54%, respectively, had measurements outside of the usual therapeutic target range. In multivariable analysis, BMI ≥25 kg/m2 (vs < 25) was associated with risk of underdiagnosis (OR 1.8 [1.2-2.8]). For undertreatment, significant adverse factors included older age ( > 35 vs ≤35y: OR 2.5 [1.2-5.1]), BMI ≥30 kg/m2 (vs < 25: OR 3.3 [1.7-6.4]), and greater perceived reliance on others for healthcare decisions (OR 1.7 [1.2-2.4]). Those with greater health-related self-efficacy were less likely to be undertreated (OR 0.5 [0.3-0.96]). Conclusions: CVRF underdiagnosis and undertreatment among childhood cancer survivors at increased risk of heart disease was common. Greater awareness among survivors and primary care providers and more aggressive control of CVRFs may mitigate this risk.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".