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Predicting suicidal behaviours using clinical instruments: Systematic review and meta-analysis of positive predictive values for risk scales

  • Gregory Carter (a1), Allison Milner (a2), Katie McGill (a1), Jane Pirkis (a3), Nav Kapur (a4) and Matthew J. Spittal (a3)...

Prediction of suicidal behaviour is an aspirational goal for clinicians and policy makers; with patients classified as ‘high risk’ to be preferentially allocated treatment. Clinical usefulness requires an adequate positive predictive value (PPV).


To identify studies of predictive instruments and to calculate PPV estimates for suicidal behaviours.


A systematic review identified studies of predictive instruments. A series of meta-analyses produced pooled estimates of PPV for suicidal behaviours.


For all scales combined, the pooled PPVs were: suicide 5.5% (95% CI 3.9–7.9%), self-harm 26.3% (95% CI 21.8–31.3%) and self-harm plus suicide 35.9% (95% CI 25.8–47.4%). Subanalyses on self-harm found pooled PPVs of 16.1% (95% CI 11.3–22.3%) for high-quality studies, 32.5% (95% CI 26.1–39.6%) for hospital-treated self-harm and 26.8% (95% CI 19.5–35.6%) for psychiatric in-patients.


No ‘high-risk’ classification was clinically useful. Prevalence imposes a ceiling on PPV. Treatment should reduce exposure to modifiable risk factors and offer effective interventions for selected subpopulations and unselected clinical populations.

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Corresponding author
Gregory Carter, Locked Bag #7, Hunter Region Mail Centre, 2301 NSW, Australia. Email:
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See editorial, pp. 384–386, this issue.

Declaration of interest

N.K. chaired the NICE guidelines for the longer term management of self-harm in England but the views in this paper are the author's own and not those of NICE or the Department of Health (UK). G.C. chaired the Royal Australian and New Zealand College of Psychiatrists' (RANZCP's) Clinical Practice Guidelines for Deliberate Self Harm but the views in this paper are the author's own and not those of the RANZCP.

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Predicting suicidal behaviours using clinical instruments: Systematic review and meta-analysis of positive predictive values for risk scales

  • Gregory Carter (a1), Allison Milner (a2), Katie McGill (a1), Jane Pirkis (a3), Nav Kapur (a4) and Matthew J. Spittal (a3)...
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Emerging consensus on the positive predictive (and clinical) value of suicide risk assessment.

Matthew Large, Psychiatrist, University of New South Wales
21 March 2017

Carter and associates recent meta-analysis [1] adds to the emerging consensus about suicide risk assessment [2, 3]. They estimated from 51 primary studies that 5.5% (95% CI 3.9-7.9%) of patients classified as high-risk can be expected to suicide over long periods of follow-up. Similarly, a 2016 meta-analysis of the suicide risk among 53 longitudinal cohorts of psychiatric patients arrived at the same suicide risk estimate for high-risk patients of 5.5%, with very similar confidence intervals (3.5-8.5%) [4]. The convergence of these two results is somewhat surprising because the differing inclusion criteria meant that each meta-analysis synthesized data from fewer than half of the primary studies included in the other. Unless there are dramatic breakthroughs in statistical modeling of suicide or new, hereto unknown, suicide risk factors, this statistic is likely to stand the test of time, meaning that 95% of high-risk patients might receive unnecessary and potentially harmful interventions for suicides that were never going to happen.


1.Carter G, Milner A, McGill K, Pirkis J, Kapur N and Spittal MJ. Predicting suicidal behaviours using clinical instruments: systematic review and meta-analysis of positive predictive values for risk scales. Br J Psychiatry. 2017.

2.Mulder R, Newton-Howes G and Coid JW. The futility of risk prediction in psychiatry. Br J Psychiatry.2016; 209: 271-2.

3.Large M and Ryan C. Suicide risk assessment: myth and reality. Int J Clin Pract. 2014; 68: 679-81.

4.Large M, Kaneson M, Myles N, Myles H, Gunaratne P and Ryan C. Meta-Analysis of Longitudinal Cohort Studies of Suicide Risk Assessment among Psychiatric Patients: Heterogeneity in Results and Lack of Improvement over Time. PloS one. 2016; 11: e0156322.

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