TY - JOUR
T1 - Prediction models for outcomes in people with low back pain receiving conservative treatment
T2 - a systematic review
AU - Vidal, Rubens
AU - Grotle, Margreth
AU - Johnsen, Marianne Bakke
AU - Yvernay, Louis
AU - Hartvigsen, Jan
AU - Ostelo, Raymond
AU - Kjønø, Lise Grethe
AU - Enstad, Christian Lindtveit
AU - Killingmo, Rikke Munk
AU - Halsnes, Einar Henjum
AU - Grande, Guilherme H.D.
AU - Oliveira, Crystian B.
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2025/1
Y1 - 2025/1
N2 - Objectives: To identify, critically appraise and evaluate the performance measures of the available prediction models for outcomes in people with low back pain (LBP) receiving conservative treatment. Study Design and Setting: In this systematic review, literature searches were conducted in Embase, Medline, and cumulative index of nursing and allied health literature from their inception until February 2024. Studies containing follow-up assessment (eg, prospective cohort studies, registry-based studies) investigating prediction models of outcomes (eg, pain intensity and disability) for people with LBP receiving conservative treatment were included. Two independent reviewers performed the study selection, the data extraction using the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies, and risk of bias assessment using the Prediction model Risk of Bias Assessment. Findings of individual studies were reported narratively taking into account the discrimination and calibration measures of the prediction models. Results: Seventy-five studies developing or investigating the validity of 216 models were included in this review. Most prediction models investigated people receiving physiotherapy treatment and most models included sociodemographic variables, clinical features, and self-reported measures as predictors. The discriminatory capacity of the internal validity of the 27 prediction models for pain intensity varied greatly showing a c-statistic ranging from 0.48 to 0.94. Similarly, the discriminatory capacity for 31 models for disability had the same pattern showing a c-statistic ranging from 0.48 to 0.86. The calibration measures of the internal validity of the prediction models predicting pain intensity and disability showed to be adequate. Only one of 3 studies testing the external validity of models to predict pain intensity and disability and reported both discrimination and calibration measures, which showed to be inadequate. The prediction models predicting the secondary outcomes (eg, self-reported recovery, quality of life, return to work) showed varied performance measures for internal validity, and only 2 studies tested the external validity of models although they did not provide performance the performance measures. Conclusion: Several prediction models have been developed for people with LBP receiving conservative treatment; however, most show inadequate discriminatory validity. A few studies externally validated the prediction models and future studies should focus on testing this before implementing in clinical practice.
AB - Objectives: To identify, critically appraise and evaluate the performance measures of the available prediction models for outcomes in people with low back pain (LBP) receiving conservative treatment. Study Design and Setting: In this systematic review, literature searches were conducted in Embase, Medline, and cumulative index of nursing and allied health literature from their inception until February 2024. Studies containing follow-up assessment (eg, prospective cohort studies, registry-based studies) investigating prediction models of outcomes (eg, pain intensity and disability) for people with LBP receiving conservative treatment were included. Two independent reviewers performed the study selection, the data extraction using the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies, and risk of bias assessment using the Prediction model Risk of Bias Assessment. Findings of individual studies were reported narratively taking into account the discrimination and calibration measures of the prediction models. Results: Seventy-five studies developing or investigating the validity of 216 models were included in this review. Most prediction models investigated people receiving physiotherapy treatment and most models included sociodemographic variables, clinical features, and self-reported measures as predictors. The discriminatory capacity of the internal validity of the 27 prediction models for pain intensity varied greatly showing a c-statistic ranging from 0.48 to 0.94. Similarly, the discriminatory capacity for 31 models for disability had the same pattern showing a c-statistic ranging from 0.48 to 0.86. The calibration measures of the internal validity of the prediction models predicting pain intensity and disability showed to be adequate. Only one of 3 studies testing the external validity of models to predict pain intensity and disability and reported both discrimination and calibration measures, which showed to be inadequate. The prediction models predicting the secondary outcomes (eg, self-reported recovery, quality of life, return to work) showed varied performance measures for internal validity, and only 2 studies tested the external validity of models although they did not provide performance the performance measures. Conclusion: Several prediction models have been developed for people with LBP receiving conservative treatment; however, most show inadequate discriminatory validity. A few studies externally validated the prediction models and future studies should focus on testing this before implementing in clinical practice.
KW - Conservative treatment
KW - Low back pain
KW - Pain management
KW - Physiotherapy
KW - Prediction models
KW - Prognosis research
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U2 - 10.1016/j.jclinepi.2024.111593
DO - 10.1016/j.jclinepi.2024.111593
M3 - Article
C2 - 39522740
AN - SCOPUS:85210298608
SN - 0895-4356
VL - 177
JO - Journal of clinical epidemiology
JF - Journal of clinical epidemiology
M1 - 111593
ER -