PMID- 28091343
OWN - NLM
STAT- MEDLINE
DCOM- 20171128
LR  - 20181202
IS  - 1469-8978 (Electronic)
IS  - 0033-2917 (Linking)
VI  - 47
IP  - 7
DP  - 2017 May
TI  - Prediction of transition to psychosis in patients with a clinical high risk for 
      psychosis: a systematic review of methodology and reporting.
PG  - 1163-1178
LID - 10.1017/S0033291716003494 [doi]
AB  - BACKGROUND: To enhance indicated prevention in patients with a clinical high risk 
      (CHR) for psychosis, recent research efforts have been increasingly directed 
      towards estimating the risk of developing psychosis on an individual level using 
      multivariable clinical prediction models. The aim of this study was to 
      systematically review the methodological quality and reporting of studies 
      developing or validating such models. METHOD: A systematic literature search was 
      carried out (up to 14 March 2016) to find all studies that developed or validated 
      a clinical prediction model predicting the transition to psychosis in CHR 
      patients. Data were extracted using a comprehensive item list which was based on 
      current methodological recommendations. RESULTS: A total of 91 studies met the 
      inclusion criteria. None of the retrieved studies performed a true external 
      validation of an existing model. Only three studies (3.5%) had an event per 
      variable ratio of at least 10, which is the recommended minimum to avoid 
      overfitting. Internal validation was performed in only 14 studies (15%) and seven 
      of these used biased internal validation strategies. Other frequently observed 
      modeling approaches not recommended by methodologists included univariable 
      screening of candidate predictors, stepwise variable selection, categorization of 
      continuous variables, and poor handling and reporting of missing data. 
      CONCLUSIONS: Our systematic review revealed that poor methods and reporting are 
      widespread in prediction of psychosis research. Since most studies relied on 
      small sample sizes, did not perform internal or external cross-validation, and 
      used poor model development strategies, most published models are probably 
      overfitted and their reported predictive accuracy is likely to be overoptimistic.
FAU - Studerus, E
AU  - Studerus E
AD  - University of Basel Psychiatric Hospital,Center for Gender Research and Early 
      Detection,Basel,Switzerland.
FAU - Ramyead, A
AU  - Ramyead A
AD  - Department of Psychiatry,Weill Institute for Neurosciences,University of 
      California (UCSF),San Francisco,CA,USA.
FAU - Riecher-Rossler, A
AU  - Riecher-Rossler A
AD  - University of Basel Psychiatric Hospital,Center for Gender Research and Early 
      Detection,Basel,Switzerland.
LA  - eng
PT  - Journal Article
PT  - Review
PT  - Systematic Review
DEP - 20170116
PL  - England
TA  - Psychol Med
JT  - Psychological medicine
JID - 1254142
SB  - IM
MH  - Biomedical Research/*standards
MH  - Humans
MH  - *Models, Theoretical
MH  - *Prognosis
MH  - Psychotic Disorders/*diagnosis
OTO - NOTNLM
OT  - Clinical high risk
OT  - prediction
OT  - prognostic models
OT  - psychosis
OT  - schizophrenia
EDAT- 2017/01/17 06:00
MHDA- 2017/11/29 06:00
CRDT- 2017/01/17 06:00
PHST- 2017/01/17 06:00 [pubmed]
PHST- 2017/11/29 06:00 [medline]
PHST- 2017/01/17 06:00 [entrez]
AID - S0033291716003494 [pii]
AID - 10.1017/S0033291716003494 [doi]
PST - ppublish
SO  - Psychol Med. 2017 May;47(7):1163-1178. doi: 10.1017/S0033291716003494. Epub 2017 
      Jan 16.