ArticleJournal of Korean medical science2026
A Longitudinal Study on Predicting Treatment Response in Depression Using Self-Reported Symptoms.
Article in Journal of Korean medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundDepression causes serious disabilities, and response to treatment is difficult to predict. This study aimed to examine whether self-reported initial symptoms can predict treatment response in depression.
methodsOne hundred fifty-seven patients who were diagnosed with mood disorders (major depressive disorder or bipolar disorder) and in a state of moderate or severe depression were recruited from six psychiatric hospitals between 2018 and 2022. Participants were classified into treatment responders (n = 89) and non-responders (n = 68) based on the Montgomery-Åsberg Depression Rating Scale, and changes in a wide range of symptoms, including anxiety and depression, were assessed using both clinician-administered scales and self-reports. Logistic regression analysis was conducted to identify factors associated with treatment response, and the performance of several prediction models using demographic information and symptom scores was compared.
resultsThere were no significant baseline differences between responders and non-responders in diagnoses, medications, clinician-rated scales, medication adherence, or objective depressive and anxiety scores. However, non-responders initially reported higher levels of obsessive-compulsive symptoms, interpersonal sensitivity, phobic anxiety, and paranoid ideation, along with lower satisfaction in social relationships. The comparison of predictive models showed that those incorporating subjective symptoms outperformed models based solely on demographic covariates (area under the receiver operating characteristic curve [AUROC] = 0.725, 95% confidence interval [CI], 0.643-0.807 vs. 0.666, 95% CI, 0.578-0.754). Notably, phobic anxiety was identified as a strong independent predictor of treatment response (odds ratio [OR], 1.93, 95% CI, 1.30-2.85).
conclusionSubjective symptoms other than depression or anxiety are important factors for predicting treatment response in depression. Therefore, incorporating patients' self-reported symptoms is crucial for predicting treatment response in depression.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.