Incidence of and Factors Associated With Nonfatal Self-injury After a Cancer Diagnosis in Ontario, Canada
Bibliographic record
Abstract
Importance: Psychological distress is a key component of patient-centered cancer care. While a greater risk of suicide among patients with cancer has been reported, more frequent consequences of distress, including nonfatal self-injury (NFSI), remain unknown. Objective: To examine the risk of NFSI after a cancer diagnosis. Design, Setting, and Participants: This population-based retrospective cohort study used linked administrative databases to identify adults diagnosed with cancer between 2007 and 2019 in Ontario, Canada. Exposures: Demographic and clinical factors. Main Outcomes and Measures: Cumulative incidence of NFSI, defined as emergency department presentation of self-injury, was computed, accounting for the competing risk of death from all causes. Factors associated with NFSI were assessed using multivariable Fine and Gray models. Results: In total, 806 910 patients met inclusion criteria. The mean (SD) age was 65.7 (14.3) years, and 405 161 patients (50.2%) were men. Overall, 2482 (0.3%) had NFSI and 182 (<0.1%) died by suicide. The 5-year cumulative incidence of NFSI was 0.27% (95% CI, 0.25%-0.28%). After adjusting for key confounders, prior severe psychiatric illness, whether requiring inpatient care (subdistribution hazard ratio [sHR], 12.6; 95% CI, 10.5-15.2) or outpatient care (sHR, 7.5; 95% CI, 6.5-8.8), and prior self-injury (sHR, 6.6; 95% CI, 5.5-8.0) were associated with increased risk of NFSI. Young adults (age 18-39 years) had the highest NFSI rates relative to individuals aged 70 years or older (sHR, 5.4; 95% CI, 4.5-6.5). The magnitude of association between prior inpatient psychiatric illness and NFSI was greatest for young adults (sHR, 17.6; 95% CI, 12.0-25.8). Certain cancer subsites were also associated with increased risk, including head and neck cancer (sHR, 1.5; 95% CI, 1.2-1.9). Conclusions and Relevance: In this study, patients with cancer had a higher incidence of NFSI than suicide after diagnosis. Younger age, history of severe psychiatric illness, and prior self-injury were independently associated with risk of NFSI. These exposures appeared to act synergistically, placing young adults with a prior mental health history at the greatest risk of NFSI. These factors should be used to identify at-risk patients.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".