Differential impact of immune-mediated inflammatory diseases before versus after cancer on patient survival: a nationwide cohort study
Bibliographic record
Abstract
OBJECTIVES: The relationship between immune-mediated inflammatory diseases (IMIDs) and cancer survival appears to be irregular and complex. However, the impact of IMIDs before vs after cancer onset on patient survival has not been clearly defined. We aimed to evaluate the relationship between IMIDs diagnosed before or after cancer onset and both all-cause and cause-specific mortality in cancer. METHODS: This nationwide cohort study utilized data from the UK Biobank, involving adults aged 37-73 years, with follow-up conducted until 31 September 2021. We assessed IMIDs diagnosed either prior to or after cancer in relation to all-cause mortality and cause-specific mortality. RESULTS: A total of 93 884 cancer participants (mean [standard deviation, SD] age: 60.2 [6.9] years; 51% female) were included in this cohort study. Compared with cancer patients without IMIDs, those with IMIDs diagnosed before cancer were associated with an increased risk of all-cause mortality (hazard ratio [HR], 1.78; 95% confidence interval [CI], 1.71-1.86) and cancer-specific mortality (HR, 1.62; 95% CI, 1.55-1.71). Conversely, those with IMIDs diagnosed after cancer exhibited protective effects on all-cause mortality (HR, 0.79; 95% CI, 0.75-0.83) and cancer mortality (HR, 0.69; 95% CI, 0.66-0.73). These findings remained consistent after conducting subgroup analyses based on the timing of immune checkpoint inhibitor introduction or using propensity score matching. We also mapped the association of individual IMIDs, both pre- and post-diagnosis, with all-cause mortality across various cancer types. IMIDs diagnosed after cancer showed diminished or reversed effects on mortality compared with those diagnosed prior to cancer. CONCLUSIONS: Our study highlights the differential impacts of IMIDs diagnosed before and after cancer onset on survival outcomes. While pre-existing IMIDs appear to exacerbate mortality risk, newly diagnosed IMIDs post-cancer may confer a survival advantage. Clinicians should consider the implications of IMIDs management in cancer patients to optimize treatment and improve overall survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".