Cognitive symptoms in major depressive disorder: associations with clinical and functional outcomes in a 6-month, non-interventional, prospective study in China

Abstract

Objective: Cognitive symptoms in major depressive disorder (MDD) are common and may negatively impact clinical and functional outcomes. The Prospective Research Observation to Assess Cognition in Treated patients with MDD (PROACT) study aimed to assess the prevalence and course of cognitive symptoms, and their associations with clinical and functional outcomes during 6 months of antidepressant treatment, in a real-world setting among Chinese patients with MDD.

Patients and methods: Outpatients (n=598) aged 18–65 years with MDD and a total score ≥17 on the Hamilton Depression Rating Scale – 17 Items (HAM-D₁₇) were observed over 6 months after initiating new antidepressant monotherapy, with follow-up visits at months 1, 2, and 6. Cognitive symptoms were assessed using the Perceived Deficits Questionnaire – Depression (PDQ-D) and cognitive performance using the Digit Symbol Substitution Test (DSST).

Results: At baseline, 76.9% of patients had indications of cognitive symptoms (PDQ-D total score ≥21); at month 6, this was reduced, but still present in 32.4%. Across the 6-month study period, patients improved across cognitive, clinical and functional assessments. High levels of cognitive symptoms (PDQ-D) consistently predicted worse clinical outcomes, ie, lower odds for remission and increased odds for relapse, as well as worse patient-reported functional outcomes and lower quality of life. In contrast, cognitive performance (DSST) predicted performance-based functioning but only a few patient-reported functional outcomes (absenteeism and quality of life), and no clinical outcomes. PDQ-D and DSST scores were uncorrelated at baseline.

Conclusion: The study highlights the importance of assessing and targeting cognitive symptoms for increasing patients’ chances of recovery and restoring functioning in the treatment of MDD. The results further highlight the relevance of complementary assessment methods to fully capture aspects of cognitive symptoms in patients with depression.

Keywords:

• MDD
• antidepressants
• cognitive performance
• real-world evidence
• PDQ-D
• DSST

Acknowledgments

The authors wish to thank all patients who took part in this study, as well as the investigators and study personnel at the following sites: Beijing An Ding Hospital, Capital Medical University; No.6 Hospital of Beijing University; Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine; The 2nd Xiangya Hospital of Central South University; West China Hospital, Sichuan University; Nanjing Brain Hospital; Beijing Huilongguan Hospital; Shenzhen Mental Health Center; The First Affiliated Hospital of Kunming Medical College; Tianjin Anding Hospital; Beijing Tian Tan Hospital; First Affiliated Hospital of Medical College of Xi’an Jiaotong University; Beijing Chaoyang Hospital; The 3rd People’s Hospital of Huzhou City; and The 3rd Hospital of Sun Yat-Sen University.

Abbreviation list

ANCOVA, analysis of covariance; CGI-S, Clinical Global Impressions – Severity of Illness; CFI, comparative fit index; DSM-5, Diagnostic and Statistical Manual of Mental Disorders, 5th Edition; DSST, Digit Symbol Substitution Test; EQ-5D, European Quality of Life Questionnaire – 5 Dimensions; HAM-D₁₇, Hamilton Depression Rating Scale – 17 Items; ICD-10, International Classification of Diseases and Related Health Problems, 10th revision; MDD, major depressive disorder; PDQ-D, Perceived Deficits Questionnaire – Depression; PHQ-9, Patient Health Questionnaire – 9 items; PROACT, the Prospective Research Observation to Assess Cognition in Treated MDD patients; RMSEA, root mean square error of approximation; SE, standard error; SEM, structural equation modeling; SDS, Sheehan Disability Scale; SRC, standardized regression coefficients; UPSA-B, University of San Diego Performance-based Skills Assessment – Brief; WPAI-SHP, Work Productivity and Activity Impairment – Specific Health Problems Questionnaire.

Data availability

The authors declare that the data supporting the findings of this study are available within the article. The authors may be contacted for further data sharing.

Supplementary materials

Selection procedure for logistic regression and ANCOVA models for clinical and functional outcomes

A series of univariate analyses were conducted for a list of candidate explanatory variables (see below), which were identified based on a literature review and clinical experience. Next, for each outcome variable, a backward stepwise procedure, ie, sequential removal of the least significant variable from the model and re-estimating the model until all independent variables were statistically significant at p<0.05, was applied on statistically significant variables (p-value <0.20) in the univariate models.

Univariate analyses with response at month 1 and remission at month 2 comprised the factors listed in i) + ii) + iii). Univariate analyses with remission and relapse at month 6 comprised the factors listed in i) + ii) + iv) + v). Univariate analyses with functional outcomes at month 6 comprised the factors listed in i) + iv).

• i) Age at baseline (18–25, 26–34, 35–54, 55–65 years); sex at baseline (male, female); region at baseline (North, South, East, West); educational level at baseline (no degree or diploma/elementary school/middle school, high school/junior college, university or above); employment status at baseline (paid employment or self-employed, unemployed/student/non-working spouse/retired/disability pension/others); at least one other concomitant mental condition at baseline (yes, no); chronic pain or fibromyalgia at baseline (yes, no).

• ii) Previous depressive episode at baseline (yes, no); at least one chronic medical condition at baseline (yes, no).

• iii) Body mass index at baseline (<30 kg/m², ≥30 kg/m²); tobacco use at baseline (yes, no); marital status at baseline (single/divorced/separated/widowed, married or living with partner); living area at baseline (rural, urban); switch of antidepressant at baseline (yes, no); duration of current depressive episode at baseline (<8 weeks, ≥8 weeks); anxiety disorder at baseline (yes, no); suicide attempt before baseline (yes, no); hospitalization for depression over the past 12 weeks before baseline (yes, no); sick-leave within 12 months before baseline (yes, no); current psychotherapy at baseline (yes, no); Clinical Global Impression Scale – Severity of Illness (CGI-S) score at baseline (1–4, 5–7); Hamilton Depression Rating Scale – 17 items (HAM-D₁₇) total score at baseline (17–23, 24–52); Patient Health Questionnaire – 9 items (PHQ-9) total score at baseline (0–4, 5–9, 10–14, 15–19, 20–27); Digit Symbol Substitution Test (DSST) score at baseline (within norm, 1/3 to 2/3 SD below norm, 2/3 to 1 SD below norm, 1 SD or more below norm); Perceived Deficits Questionnaire – Depression (PDQ-D) total score at baseline (0-Q1, Q1-median, median-Q3, Q3–80); Work Productivity and Activity Impairment – Specific Health Problems (WPAI-SHP) Activity impairment at baseline (continuous); European Quality of Life Questionnaire – 5 Dimensions (EQ-5D) utility score at baseline (continuous).

• iv) Suicide attempt before baseline or between baseline and month 2 (yes, no); hospitalization for depression over the past 12 weeks before baseline or between baseline and month 2 (yes, no); sick-leave within 12 months before baseline or between baseline and month 2 (yes, no); treatment line at month 2 (1, ≥2); discontinuation of antidepressant treatment between baseline and month 2 (yes, no); CGI-S score at month 2 (1–3, 4, 5–7); HAM-D₁₇ total score at month 2 (0–7, 8–16 17–23, 24–52); PHQ-9 total score at month 2 (0–4, 5–9, 10–14, 15–19, 20–27); DSST score at month 2 (within norm, 1/3 to 2/3 SD below norm, 2/3 to 1 SD below norm, 1 SD or more below norm); PDQ-D total score at month 2 (0-Q1, Q1-median, median-Q3, Q3–80).

• v) Previous or current psychotherapy at baseline (yes, no); WPAI–SHP Activity impairment at month 2 (continuous); EQ-5D utility score at month 2 (continuous).

Replacement of missing values for coding of relapse

PHQ-9 total score ≤9 points at month 2: replaced with month 2 HAM-D₁₇ total score ≤7 if month 2 PHQ-9 total score was missing, or with month 2 CGI-S score ≤2 if month 2 HAM-D₁₇ was missing; PHQ-9 total score ≥10 points at month 6: replaced with month 6 HAM-D₁₇ total score ≥17 if month 6 PHQ-9 total score was missing, or with month 6 CGI-S score ≥4 if month 6 HAM-D₁₇ was missing; PHQ-9 total score ≤9 points at month 2 and month 6: replaced with HAM-D₁₇ total score <17 if PDQ-9 for these timepoints was missing, or with CGI-S score <4 if HAM-D₁₇ was missing.

Disclosure

The analyses reported in this paper were presented at the 31st European College of Neuropsychopharmacology Annual Meeting 2018 as poster presentations with interim findings. Posters’ abstracts were published in European Neuropsychopharmacology 2019: www.sciencedirect.com/journal/european-neuropsychopharmacology/vol/29/suppl/S1.

H. Lundbeck A/S and Lundbeck China sponsored the study and supported this publication.

G Wang has received honoraria for being an advisor to or providing educational talks for Lundbeck, Pfizer, Sumitomo, Janssen and Janssen, and Eli Lilly company.

TM Si has been a consultant and/or advisor to Janssen Research and Development (Beijing), Pfizer, Lundbeck, and Otsuka. She received honoraria and/or grant support from Janssen Research and Development (Beijing), Lundbeck, Pfizer, and Otsuka.

CX Wang has received honoraria for being an advisor to or providing educational talks for Lundbeck, Lilly and Pfizer Company.

LN Wang has received honoraria for being an advisor to or providing educational talks for Lundbeck, Pfizer, Sumitomo, Eli Lilly Company.

Y Fang has been a consultant and/or advisor to Janssen & Janssen, Pfizer, Lundbeck, Eli Lilly, and Otsuka. He received grant support from Eli Lilly Company.

L Li has received honoraria for being an advisor to or providing educational talks for Lundbeck, Pfizer, Janssen Company.

A Ettrup and HLF Eriksen are full-time employees of Lundbeck. KHX Tan and L Ge were full-time employees of Lundbeck Singapore and Lundbeck China, respectively, at the time of study conduct.

The authors report no other conflicts of interest in this work.