Defining and Assessing International Classification of Disease Suicidality Phenotypes for Genetic Studies
Bibliographic record
Abstract
Background: Suicidality, including suicidal ideation (SI), attempt (SA), and death (SD), represents complex and partially overlapping phenotypes. This complexity contributes to study population heterogeneity in suicidality research, impeding replication efforts and data consolidation by research consortia. The standardization of suicidality definitions would help but has been insufficiently addressed in existing literature. Here, the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) provides International Classification of Disease (ICD) definitions, a critical real-world data source, for SA and SI. Methods: The PGC Suicide Workgroup used published definitions coupled with expert consensus to develop ICD lists to serve as suicidality phenotype definitions. One SI and two SA lists were produced and evaluated for performance against patient screening responses in two independent cohorts (N = 9,151 and 12,621) with differing ascertainment strategies. Outcomes: ICD list suicidality definitions were produced. Evaluation of generated ICD lists versus patient responses across two cohorts demonstrated varied sensitivity (15·4% to 71·1%), specificity (67·6% to 96·3%), and positive predictive values (0·57-0·92). SI ICD code performance also varied in sensitivity (29·4%-86·1%), specificity (64·2% to 90·6%), and positive predictive values (0·67 to 0·98). Interpretation: Guidelines were developed to provide more consistent and comparable suicidality definitions. However, real-world application of ICD codes leads to a wide range of performance, dependent on cohort characteristics, that will need to be carefully considered in implementation. Future efforts would benefit from consistent training in use of ICD codes between sites to improve generalizability, and should include validation in diverse populations. Funding: This work was funded by NIMH R01MH132733 (Mullins), R01MH132733 (Ruderfer), R01MH123619 (Docherty), R01MH123489 (Coon), R01MH124839 (PGC4), R01MH118233 and MH117599 (Smoller), Brain and Behavior Research Foundation No. 31248 (Monson), the Huntsman Mental Health Institute, National Science Foundation Graduate Research Fellowship Program Grant #1842169, and by grant # I01BX005881 and #IK6BX006523 (Kimbrel) from the Department of Veterans Affairs.
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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 | 0.073 | 0.135 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".