A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings

The factor structure of the Patient Health Questionnaire-9 in stroke: A comparison with a non-stroke population

Background: It is unclear if certain post-stroke somatic symptoms load onto items of the Patient Health Questionnaire-9 (PHQ-9), a self-report depression questionnaire. We investigated these concerns in a stroke sample using factor analysis, benchmarked against a non-stroke comparison group. Methods: The secondary dataset constituted 787 stroke and 12,016 non-stroke participants. A subsample of 1574 comparison participants was selected via propensity score matching. Dimensionality was assessed by comparing fit statistics of one-factor, two-factor, and bi-factor models. Between-group differences in factor structure were explored using measurement invariance. Results: A two-factor model, consisting of somatic and cognitive-affective factors, showed better fit than the unidimensional model (CFI = 0.984 versus CFI = 0.974, p <.001), but the high correlation between the factors indicated unidimensionality (r = 0.866). Configural invariance between stroke and non-stroke was supported (CFI = 0.983, RMSEA = 0.080), as were invariant thresholds (p =.092) and loadings (p =.103). Strong invariance was violated (p <.001, ΔCFI = −0.003), stemming from differences in the tiredness and appetite intercepts. These differences resulted in a moderate overestimation of depression in stroke when using a summed score approach, relative to the comparison sample (Cohen's d = 0.434). Conclusions: The findings suggest that the PHQ-9 measures a single factor in stroke. Because stroke patients may report higher tiredness on item 4, caution is advisable when classifying patients as depressed if they are near the cut-off and have significant post-stroke fatigue. Caution is also advised when comparing total scores between stroke and other populations

A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings

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

Data-driven cutoff selection for the patient health questionnaire-9 depression screening tool

Importance: Test accuracy studies often use small datasets to simultaneously select an optimal cutoff score that maximizes test accuracy and generate accuracy estimates. Objective: To evaluate the degree to which using data-driven methods to simultaneously select an optimal Patient Health Questionnaire-9 (PHQ-9) cutoff score and estimate accuracy yields (1) optimal cutoff scores that differ from the population-level optimal cutoff score and (2) biased accuracy estimates. Design, Setting, and Participants: This study used cross-sectional data from an existing individual participant data meta-analysis (IPDMA) database on PHQ-9 screening accuracy to represent a hypothetical population. Studies in the IPDMA database compared participant PHQ-9 scores with a major depression classification. From the IPDMA population, 1000 studies of 100, 200, 500, and 1000 participants each were resampled. Main Outcomes and Measures: For the full IPDMA population and each simulated study, an optimal cutoff score was selected by maximizing the Youden index. Accuracy estimates for optimal cutoff scores in simulated studies were compared with accuracy in the full population. Results: The IPDMA database included 100 primary studies with 44 503 participants (4541 [10%] cases of major depression). The population-level optimal cutoff score was 8 or higher. Optimal cutoff scores in simulated studies ranged from 2 or higher to 21 or higher in samples of 100 participants and 5 or higher to 11 or higher in samples of 1000 participants. The percentage of simulated studies that identified the true optimal cutoff score of 8 or higher was 17% for samples of 100 participants and 33% for samples of 1000 participants. Compared with estimates for a cutoff score of 8 or higher in the population, sensitivity was overestimated by 6.4 (95% CI, 5.7-7.1) percentage points in samples of 100 participants, 4.9 (95% CI, 4.3-5.5) percentage points in samples of 200 participants, 2.2 (95% CI, 1.8-2.6) percentage points in samples of 500 participants, and 1.8 (95% CI, 1.5-2.1) percentage points in samples of 1000 participants. Specificity was within 1 percentage point across sample sizes. Conclusions and Relevance: This study of cross-sectional data found that optimal cutoff scores and accuracy estimates differed substantially from population values when data-driven methods were used to simultaneously identify an optimal cutoff score and estimate accuracy. Users of diagnostic accuracy evidence should evaluate studies of accuracy with caution and ensure that cutoff score recommendations are based on adequately powered research or well-conducted meta-analyses

Literature review of cancer mortality and incidence among dentists

This review assesses the epidemiological literature describing dentist mortality and cancer incidence risk. In the dental workplace a variety of hazards may have been historically present or currently exist which can impact dentists' long‐term health, including their mortality and cancer incidence. The epidemiological literature of dentistry's health outcomes was reviewed with a focus on all cancers combined and cancers of the brain, lung, reproductive organs and skin. Relevant studies were identified using MEDLINE and NIOSHTIC through early 2006 and from references cited in the articles obtained from these databases. Dentist cancer mortality and incidence generally showed a favourable risk pattern for lung cancer and overall cancer occurrence. Nevertheless, several studies reported an increased risk for certain cancers, such as those of the skin and, to a lesser extent, the brain and female breast. These elevated risks may be related to social status or education level, or may alternatively represent the impact of hazards in the workplace. The evidence for an increased mortality or cancer incidence risk among dentists must be interpreted in light of methodological limitations of published studies. Future studies of dentists would benefit from the assessment of specific occupational exposures rather than relying on job title alone

Characteristics and Comorbid Symptoms of Older Adults Reporting Death Ideation

OBJECTIVE:: To determine whether death ideation in late life is associated with markers of elevated risk for suicide, or reflects normal psychological processes in later life. DESIGN/SETTING:: Population-based cross-sectional study in Gothenburg, Sweden. PARTICIPANTS:: The sample consists of 345 men and women of age 85 years (born 1901-1902) and living in Gothenburg, Sweden. MAIN OUTCOME MEASURES:: The Paykel Scale measured the most severe level of suicidality over an individual's lifetime. Other key measures were severity of depression and anxiety and frequency of death/suicidal ideation over the previous month. RESULTS:: Latent class analysis revealed distinct groups of older adults who reported recent death ideation. Recent death ideation did not occur apart from other risk factors for suicide; instead individuals reporting recent death ideation also reported either 1) recent high levels of depression and anxiety, or 2) more distant histories of serious suicidal ideation (indicative of worst point severity of suicidal ideation)-both of which elevate risk for eventual suicide. CONCLUSIONS:: Our results indicate a heterogeneous presentation of older adults who report death ideation, with some presenting with acute distress and suicidal thoughts, and others presenting with low distress but histories of serious suicidal ideation. The presence of death ideation is associated with markers of increased risk for suicide, including "worst point" active suicidal ideation

Nursing Home Residents with Dementia Experience Better End‐of‐Life Care and Outcomes in Nursing Homes with Alzheimer’s Special Care Units

RESEARCH OBJECTIVE: Nursing homes (NHs) are critical end‐of‐life (EOL) care settings for 70% of Americans dying with Alzheimer’s disease/related dementia (ADRD). Associations between facility‐level organization of care, including presence of Alzheimer’s special care units (ASCUs), and EOL care quality in NHs are unclear. Our objective was to examine variations in EOL care/outcomes (in‐hospital/NH death, death with pressure ulcers, potentially avoidable hospitalizations (PAHs), and hospice use in the last 90 days of life) among residents who died with mild, moderate, or severe ADRD in NHs with/without ASCUs. STUDY DESIGN: We used descriptive analyses and multivariate logistic regression models, adjusting for resident, NH, county, and state‐level factors, to examine associations between EOL care/outcomes and presence of ASCUs among NH decedents with ADRD. POPULATION STUDIED: We used CY2016‐2017 national Medicare claims data and the Minimum Data Set (MDS) to identify long‐stay NH residents with ADRD who died in 2017. The sample included residents who died in a NH or hospital shortly following NH discharge, were not comatose, and were at least 65 years old at time of death. We used ICD‐10 diagnosis codes and the cognitive function scale to determine ADRD presence and severity. Medicare claims, the MDS, and several public data sets were used to assess EOL quality and identify resident, NH, and market‐level covariates. The study sample included 191 435 decedents with ADRD from 14 618 NHs. PRINCIPAL FINDINGS: As severity of ADRD increased, adjusted rates of in‐hospital death and PAHs decreased (17.2%‐6.4% for in‐hospital death; 12.0%‐7.3% for PAHs; P‐values:< 0.001), while adjusted rates of dying with pressure ulcers and hospice use increased (8.4%‐13.7% for deaths with pressure ulcers; 23.4%‐39.7% for hospice use; P‐values:< 0.001). Presence of ASCUs lowered the adjusted rate of in‐hospital death (3.7%, 2.2%, 2.5%; P‐values:< 0.001), dying with pressure ulcers (0.6%, 2.1%, 4.3%; P‐values:< 0.001), and PAHs (1.8%, 1.5%, 2.3%; P‐values:< 0.001) among decedents with mild, moderate, and severe ADRD, respectively. Adjusted rates of hospice use were not as clinically significant or consistent across decedents with differing levels of ADRD severity. Decedents in for‐profit NHs with ASCUs had higher odds of in‐hospital death (OR:1.17; P‐value: 0.032) and hospice use (OR:1.19; P‐value: 0.030). In NHs with ASCUs, higher skilled nurse staffing was associated with lower odds of PAHs (OR:0.07; P‐value: 0.002) and hospice use (OR:0.16; P‐value:< 0.001). In more competitive NH markets, presence of ASCUs was associated with higher odds of hospice use (ORs: 1.74, 1.33; P‐values:< 0.001, 0.035). CONCLUSIONS: NH decedents with ADRD residing in NHs with ASCUs were consistently more likely to die in NHs rather than in hospital and had fewer pressure ulcers and PAHs at EOL. IMPLICATIONS FOR POLICY OR PRACTICE: Our findings suggest that presence of ASCUs may create environments in which better outcomes are possible for residents dying with ADRD. However, because there is no definition as to what constitutes ASCUs, it is difficult to identify specific dimensions promoting better care. Future research to understand NH practice/care processes associated with presence of ASCUs is needed to identify possible interventions/policy initiatives to increase ASCU presence. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality