A198 PERSONALIZING THE AGE TO STOP COLORECTAL CANCER SCREENING IN CANADA BASED ON COMORBIDITY AND PRIOR SCREENING HISTORY: MODEL ESTIMATES OF HARMS AND BENEFITS
Bibliographic record
Abstract
The Canadian Task Force on Preventive Health Care recommends against screening individuals at average risk of colorectal cancer (CRC) after age 74. However, harms and benefits of screening may depend on age, sex, comorbidities and prior screening history. To determine stop ages for CRC screening with faecal immunochemical testing (FIT) based on sex, comorbidity and prior screening history. We used the Microsimulation Screening Analysis-Colon (MISCAN-Colon) model to simulate a cohort of Canadian citizens born in 1960. The model was used to estimate the harms and benefits of undergoing one more CRC screen in males and females, aged 66 to 90 years by comorbidity status (no, low, moderate or severe) and previous screening history (no, 50% (adequate) and 100% (perfect) adherence). Screening was assumed to occur in an organized CRC screening program using biennial FIT. In order to determine the stop age that results in an acceptable balance between harms and benefits, we compared the harms and benefits for each cohort to that of an average health Canadian population, who had perfect prior screening, undergoing one more screening event at 74 years of age. We present the incremental number needed to screen to gain one additional life year per 1,000 screened individuals compared to the threshold, defined by stopping screening at 74 years and 76 years in the healthy, average risk population with a history of perfect prior screening. Using the threshold described above, previously unscreened men and women with no comorbidity can be screened up until the age of 88 years. As comorbidity increased, the age to stop screening decreased for both males and females. For those with no or low comorbidity, as prior screening compliance improved, the age to stop screening decreased. For example, those with no comorbidity and adequate or perfect prior screening should stop screening at 80 and 76 years of age, respectively. Participants with severe comorbidity had the lowest age to stop screening (age 66 or lower) which did not vary by prior screening history (see Table). The stopping age for CRC screening using biennial FIT can be personalized based on the participant’s comorbidities and prior screening history; sex appears to have limited impact on screening stop age. Patients and providers can use these findings for decision-making regarding screening. Policy makers may wish to consider them in the design of organized CRC screening programs. Suggested stop ages by prior screening & comorbidity CM=comorbidity Cancer Care Ontario
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".