Are more responsive depression scales really superior depression scales?

Scalable Screening and Treatment Response Monitoring for Perinatal Depression in Low- and Middle-Income Countries

Common perinatal mental disorders such as anxiety and depression are a public health concern in low- and middle-income countries. Several tools exist for screening and monitoring treatment responses, which have frequently been tested globally in clinical and research settings. However, these tools are relatively long and not practical for integration into routine data systems in most settings. This study aims to address this gap by considering three short tools: The Community Informant Detection Tool (CIDT) for the identification of women at risk, the 4-item Patient Health Questionnaire (PHQ-4) for screening women at high-risk, and the 4-item Hamilton Depression Rating Scale (HAMD-4) for measuring treatment responses. Studies in rural Pakistan showed that the CIDT offered a valid and reliable key-informant approach for the detection of perinatal depression by utilizing a network of peers and local health workers, yielding a sensitivity of 97.5% and specificity of 82.4%. The PHQ-4 had excellent psychometric properties to screen women with perinatal depression through trained community health workers, with a sensitivity of 93.4% and specificity of 91.70%. The HAMD-4 provided a good model fit and unidimensional construct for assessing intervention responses. These short, reliable, and valid tools are scalable and expected to reduce training, administrative and human resource costs to health systems.

Diagnosis Accuracy of Baptista Depression Scale: Adult and Screening Versions

Abstract This study aimed to investigate the diagnostic accuracy of the Baptista Depression Scale adult and screening versions (EBADEP-A and EBADEP-screening) for discrimination of people with a major depressive episode (MDE) or major depressive disorder (MDD) and to compare discriminative capacities. Participants were 187 people, 52 patients, and 135 non-clinical individuals. Results indicated sensitivity equal to 0.92 and specificity equal to 0.88 for EBADEP-A (cut-off = 54), and 0.96 and 0.82, respectively, for EBADEP-screening (cut-off = 17). Findings suggest equivalence between the two versions of EBADEP to discriminate people with MDE or MDD. Results indicate that the two versions can provide a correct diagnostic indicative for MDE and MDD.

Understanding personalized dynamics to inform precision medicine: a dynamic time warp analysis of 255 depressed inpatients

BACKGROUND

Major depressive disorder (MDD) shows large heterogeneity of symptoms between patients, but within patients, particular symptom clusters may show similar trajectories. While symptom clusters and networks have mostly been studied using cross-sectional designs, temporal dynamics of symptoms within patients may yield information that facilitates personalized medicine. Here, we aim to cluster depressive symptom dynamics through dynamic time warping (DTW) analysis.

METHODS

The 17-item Hamilton Rating Scale for Depression (HRSD-17) was administered every 2 weeks for a median of 11 weeks in 255 depressed inpatients. The DTW analysis modeled the temporal dynamics of each pair of individual HRSD-17 items within each patient (i.e., 69,360 calculated "DTW distances"). Subsequently, hierarchical clustering and network models were estimated based on similarities in symptom dynamics both within each patient and at the group level.

RESULTS

The sample had a mean age of 51 (SD 15.4), and 64.7% were female. Clusters and networks based on symptom dynamics markedly differed across patients. At the group level, five dynamic symptom clusters emerged, which differed from a previously published cross-sectional network. Patients who showed treatment response or remission had the shortest average DTW distance, indicating denser networks with more synchronous symptom trajectories.

CONCLUSIONS

Symptom dynamics over time can be clustered and visualized using DTW. DTW represents a promising new approach for studying symptom dynamics with the potential to facilitate personalized psychiatric care.

Efficacy of new-generation antidepressants assessed with the Montgomery-Asberg Depression Rating Scale, the gold standard clinician rating scale: A meta-analysis of randomised placebo-controlled trials

BACKGROUND

It has been claimed that efficacy estimates based on the Hamilton Depression Rating-Scale (HDRS) underestimate antidepressants true treatment effects due to the instrument's poor psychometric properties. The aim of this study is to compare efficacy estimates based on the HDRS with the gold standard procedure, the Montgomery-Asberg Depression Rating-Scale (MADRS).

METHODS AND FINDINGS

We conducted a meta-analysis based on the comprehensive dataset of acute antidepressant trials provided by Cipriani et al. We included all placebo-controlled trials that reported continuous outcomes based on either the HDRS 17-item version or the MADRS. We computed standardised mean difference effect size estimates and raw score drug-placebo differences to evaluate thresholds for clinician-rated minimal improvements (clinical significance). We selected 109 trials (n = 32,399) that assessed the HDRS-17 and 28 trials (n = 11,705) that assessed the MADRS. The summary estimate (effect size) for the HDRS-17 was 0.27 (0.23 to 0.30) compared to 0.30 (0.22 to 0.38) for the MADRS. The effect size difference between HDRS-17 and MADRS was thus only 0.03 and not statistically significant according to both subgroup analysis (p = 0.47) and meta-regression (p = 0.44). Drug-placebo raw score difference was 2.07 (1.76 to 2.37) points on the HDRS-17 (threshold for minimal improvement: 7 points according to clinician-rating and 4 points according to patient-rating) and 2.99 (2.24 to 3.74) points on the MADRS (threshold for minimal improvement: 8 points according to clinician-rating and 5 points according to patient-rating).

CONCLUSIONS

Overall there was no meaningful difference between the HDRS-17 and the MADRS. These findings suggest that previous meta-analyses that were mostly based on the HDRS did not underestimate the drugs' true treatment effect as assessed with MADRS, the preferred outcome rating scale. Moreover, the drug-placebo differences in raw scores suggest that treatment effects are indeed marginally small and with questionable importance for the average patient.