Disparities in cancer screening in people with mental illness across the world versus the general population: prevalence and comparative meta-analysis including 4 717 839 people
Bibliographic record
Abstract
Background Since people with mental illness are more likely to die from cancer, we assessed whether people with mental illness undergo less cancer screening compared with the general population. Methods In this systematic review and meta-analysis, we searched PubMed and PsycINFO, without a language restriction, and hand-searched the reference lists of included studies and previous reviews for observational studies from database inception until May 5, 2019. We included all published studies focusing on any type of cancer screening in patients with mental illness; and studies that reported prevalence of cancer screening in patients, or comparative measures between patients and the general population. The primary outcome was odds ratio (OR) of cancer screening in people with mental illness versus the general population. The Newcastle-Ottawa Scale was used to assess study quality and I 2 to assess study heterogeneity. This study is registered with PROSPERO, CRD42018114781. Findings 47 publications provided data from 46 samples including 4 717 839 individuals (501 559 patients with mental illness, and 4 216 280 controls), of whom 69·85% were women, for screening for breast cancer (k=35; 296 699 individuals with mental illness, 1 023 288 in the general population), cervical cancer (k=29; 295 688 with mental illness, 3 540 408 in general population), colorectal cancer (k=12; 153 283 with mental illness, 2 228 966 in general population), lung and gastric cancer (both k=1; 420 with mental illness, none in general population), ovarian cancer (k=1; 37 with mental illness, none in general population), and prostate cancer (k=6; 52 803 with mental illness, 2 038 916 in general population). Median quality of the included studies was high at 7 (IQR 6–8). Screening was significantly less frequent in people with any mental disease compared with the general population for any cancer (k=37; OR 0·76 [95% CI 0·72–0·79]; I 2 =98·53% with publication bias of Egger's p value=0·025), breast cancer (k=27; 0·65 [0·60–0·71]; I 2 =97·58% and no publication bias), cervical cancer (k=23; 0·89 [0·84–0·95]; I 2 =98·47% and no publication bias), and prostate cancer (k=4; 0·78 [0·70–0·86]; I 2 =79·68% and no publication bias), but not for colorectal cancer (k=8; 1·02 [0·90–1·15]; I 2 =97·84% and no publication bias). Interpretation Despite the increased mortality from cancer in people with mental illness, this population receives less cancer screening compared with that of the general population. Specific approaches should be developed to assist people with mental illness to undergo appropriate cancer screening, especially women with schizophrenia. Funding None.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.053 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".