Prevalence of suicidal behaviour following traumatic brain injury: Longitudinal follow-up data from the NIDRR Traumatic Brain Injury Model Systems

Objective: This study utilized the Traumatic Brain Injury Model Systems (TBIMS) National Database to examine the prevalence of depression and suicidal behaviour in a large cohort of patients who sustained moderate-to-severe TBI. Method: Participants presented to a TBIMS acute care hospital within 72 hours of injury and received acute care and comprehensive rehabilitation in a TBIMS designated brain injury inpatient rehabilitation programme. Depression and suicidal ideation were measured with the Patient Health Questionnaire (PHQ-9). Self-reported suicide attempts during the past year were recorded at each follow-up examination, at 1, 2, 3, 10, 15 and 20 years post-injury. Results: Throughout the 20 years of follow-up, rates of depression ranged from 24.8–28.1%, suicidal ideation ranged from 7.0–10.1% and suicide attempts (past year) ranged from 0.8–1.7%. Participants who endorsed depression and/or suicidal behaviour at year 1 demonstrated consistently elevated rates of depression and suicidal behaviour 5 years after TBI. Conclusion: Compared to the general population, individuals with TBI are at greater risk for depression and suicidal behaviour many years after TBI. The significant psychiatric symptoms evidenced by individuals with TBI highlight the need for routine screening and mental health treatment in this population

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis.

OBJECTIVES: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores ≥10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 ≥10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence. STUDY DESIGN AND SETTING: Individual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status. RESULTS: A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 ≥10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%); pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%); and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 ≥10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 ≥14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 ≥14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%). CONCLUSION: PHQ-9 ≥10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in individual studies

Probability of major depression diagnostic classification using semi-structured vs. fully structured diagnostic interviews

Background: Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification. Aims: To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics. Method: Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analyzed. Binomial Generalized Linear Mixed Models were fit. Results: 17,158 participants (2,287 major depression cases) from 57 primary studies were analyzed. Among fully structured interviews, odds of major depression were higher for the MINI compared to the Composite International Diagnostic Interview (CIDI) [OR (95% CI) = 2.10 (1.15-3.87)]. Compared to semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores 6) as having major depression [OR (95% CI) = 3.13 (0.98-10.00)], similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) [OR (95% CI) = 0.96 (0.56-1.66)], and significantly less likely for high-level symptoms (PHQ-9 scores 16) [OR (95% CI) = 0.50 (0.26-0.97)]. Conclusions: The MINI may identify more depressed cases than the CIDI, and semi- and fully structured interviews may not be interchangeable methods, but these results should be replicated

Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis

Objective: To determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression. Design: Individual participant data meta-analysis. Data sources: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-February 2015). Inclusion criteria: Eligible studies compared PHQ-9 scores with major depression diagnoses from validated diagnostic interviews. Primary study data and study level data extracted from primary reports were synthesized. For PHQ-9 cut-off scores 5-15, bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, among studies that used semistructured diagnostic interviews, which are designed for administration by clinicians; fully structured interviews, which are designed for lay administration; and the Mini International Neuropsychiatric (MINI) diagnostic interviews, a brief fully structured interview. Sensitivity and specificity were examined among participant subgroups and, separately, using meta-regression, considering all subgroup variables in a single model. Results: Data were obtained for 58 of 72 eligible studies (total n=17 357; major depression cases n=2312). Combined sensitivity and specificity was maximized at a cut-off score of 10 or above among studies using a semistructured interview (29 studies, 6725 participants; sensitivity 0.88, 95% confidence interval 0.83 to 0.92; specificity 0.85, 0.82 to 0.88). Across cut-off scores 5-15, sensitivity with semistructured interviews was 5-22% higher than for fully structured interviews (MINI excluded; 14 studies, 7680 participants) and 2-15% higher than for the MINI (15 studies, 2952 participants). Specificity was similar across diagnostic interviews. The PHQ-9 seems to be similarly sensitive but may be less specific for younger patients than for older patients; a cut-off score of 10 or above can be used regardless of age.. Conclusions: PHQ-9 sensitivity compared with semistructured diagnostic interviews was greater than in previous conventional meta-analyses that combined reference standards. A cut-off score of 10 or above maximized combined sensitivity and specificity overall and for subgroups. Registration: PROSPERO CRD42014010673

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Rehabilitation and Depression: Spinal Cord Injury and Traumatic Brain Injury

Learning Objectives Recall what are the base rates of and risk factors for major depressive disorder (MDD) in spinal cord injury (SCI) and traumatic brain injury (TBI) Describe an efficient, evidence-based method to screen for MDD and monitor response to treatment in people with TBI or SCI Summarize the evidence for medical and psychosocial treatments of MDD in TBI and SCI Overview Prevalence of major depressive disorder (MDD) in people with traumatic brain injury (TBI) or spinal cord injury (SCI) Current treatment adquacy Ways to improve identification of MDD Treatment efficacy - Medical, Psychological, Physical Activity Future directions of summar