Evidence map›Paper›PMID 41469616›Full record

ArticleBMC psychiatry2025

Prognostic prediction in schizophrenia using the Anderson-Gill time-dependent Cox model: a cohort study in a less-developed region of Southwest China.

Weiqi Tang, Mingsong Li, Zhongxin Hou, Ensheng Pu, Nan Cheng, Li Deng, Shifan He, Dejue Men, Jinglin Huang, Yi Li and 4 more

Abstract read
In one paragraph

Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Weiqi Tang *School of Public Health, Kunming Medical University, Kunming, China.
Mingsong Li *Baoshan Center for Disease Control and Prevention, Baoshan, China.
Zhongxin HouZhangdian District Center for Disease Control and Prevention, Zibo, China.
Ensheng PuThe Third People's Hospital of Baoshan & Baoshan Mental Health Center, Baoshan, China.
Nan ChengSchool of Public Health, Kunming Medical University, Kunming, China.
Li DengBaoshan Center for Disease Control and Prevention, Baoshan, China.
Shifan HeSchool of Public Health, Kunming Medical University, Kunming, China.
Dejue MenSchool of Public Health, Kunming Medical University, Kunming, China.
Jinglin HuangSchool of Public Health, Kunming Medical University, Kunming, China.
Yi LiXuanwei Hospital of Traditional Chinese Medicine, Xuanwei, China.
Qian WangSchool of Public Health, Kunming Medical University, Kunming, China.
Jianzhong YinSchool of Public Health, Kunming Medical University, Kunming, China. yinjianzhong2005@sina.com.
Qiong MengSchool of Public Health, Kunming Medical University, Kunming, China. mengqiong2006@163.com.
Teng ZhangSchool of Economics and Management, Baoshan University, No. 16, Yuanzheng Road, Longyang District, Baoshan City, Yunnan Province, 678000, China. 383910587@qq.com.

Funding

First-Class Discipline Team of Kunming Medical University 2024XKTDTS15National Natural Science Foundation of China 82560663
6 · The paper itself

Abstract

backgroundSchizophrenia represents a significant global public health burden, with considerable impact on morbidity and mortality. This study sought to construct a prognostic model to estimate mortality risk in individuals diagnosed with schizophrenia, employing a Cox proportional hazards framework with time-dependent variables.

methodsParticipants were recruited from a cohort of individuals with schizophrenia in a less-developed area of Southwest China and followed for a median of 6.4 years. A time-dependent Cox model based on the Anderson-Gill method was established to predict survival, followed by comprehensive model evaluation and graphical presentation.

resultsA total of 1,009 participants were enrolled, with 86 deaths recorded during follow-up. The model identified female sex (HR = 0.599, 95%CI= [0.387-0.928]) and hospitalization (HR = 0.499, 95%CI= [0.251-0.992]) as protective factors. Higher social function scores were associated with reduced mortality risk (HR = 0.889, 95%CI= [0.793-0.995]). Conversely, poor sleep quality (HR = 3.824, 95%CI= [1.482-9.867]) and abnormal electrocardiographic findings (HR = 2.185, 95%CI= [1.236-3.862]) increased mortality risk. Each additional year of age at initial diagnosis corresponded to an elevated risk of death (HR = 1.044, 95%CI= [1.027-1.060]). Model performance was robust, with a concordance index (C-index) of 0.820. Time-dependent AUC values at 1, 3, and 5 years were 0.814, 0.848, and 0.831, respectively.

conclusionsMortality risk among individuals with schizophrenia was significantly associated with sex, hospitalization status, social functioning, age at diagnosis, sleep quality, and electrocardiographic abnormalities. The model demonstrated strong predictive accuracy, and the accompanying nomogram together with the Excel-based scoring system offers a practical tool for rapid clinical risk assessment, supporting timely implementation of targeted interventions to improve patient outcomes. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

SchizophreniaAdultChinaCohort StudiesFemaleHospitalizationHumansMaleMiddle AgedPrognosisProportional Hazards ModelsRisk FactorsSex FactorsLess-developed regionPrediction modelPrognosisSchizophrenia

Identifiers

PMID41469616
PMCPMC12895740

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Registered trials

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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.