{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:33:12Z","timestamp":1787009592543,"version":"build-2736575974"},"reference-count":48,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2023,9,26]],"date-time":"2023-09-26T00:00:00Z","timestamp":1695686400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Horizon 2020 Research and Innovation Program","award":["777090"],"award-info":[{"award-number":["777090"]}]},{"name":"National Institute for Health Research under its Programme Grants for Applied Research scheme","award":["RP-PG-1211-20010"],"award-info":[{"award-number":["RP-PG-1211-20010"]}]},{"name":"Centre of Excellence funding from Versus Arthritis","award":["20202"],"award-info":[{"award-number":["20202"]}]},{"name":"National Institute for Health and Care Research School for Primary Care Research","award":["390"],"award-info":[{"award-number":["390"]}]},{"name":"National Institute for Health and Care Research Birmingham Biomedical Research Centre"},{"name":"University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham"},{"name":"National Institute for Health and Care Research School for Primary Care Research"},{"name":"National Institute for Health and Care Research senior investigator"},{"name":"National Institute for Health and Care Research Research Professorship","award":["NIHR-RP-011-015"],"award-info":[{"award-number":["NIHR-RP-011-015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The purpose of this study was to develop and externally validate multivariable prediction models for future pain intensity outcomes to inform targeted interventions for patients with neck or low back pain in primary care settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Model development data were obtained from a group of 679 adults with neck or low back pain who consulted a participating United Kingdom general practice. Predictors included self-report items regarding pain severity and impact from the STarT MSK Tool. Pain intensity at 2 and 6\u00a0months was modeled separately for continuous and dichotomized outcomes using linear and logistic regression, respectively. External validation of all models was conducted in a separate group of 586 patients recruited from a similar population with patients\u2019 predictor information collected both at point of consultation and 2 to 4\u00a0weeks later using self-report questionnaires. Calibration and discrimination of the models were assessed separately using STarT MSK Tool data from both time points to assess differences in predictive performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Pain intensity and patients reporting their condition would last a long time contributed most to predictions of future pain intensity conditional on other variables. On external validation, models were reasonably well calibrated on average when using tool measurements taken 2 to 4\u00a0weeks after consultation (calibration slope\u2009=\u20090.848 [95% CI\u2009=\u20090.767 to 0.928] for 2-month pain intensity score), but performance was poor using point-of-consultation tool data (calibration slope for 2-month pain intensity score of 0.650 [95% CI\u2009=\u20090.549 to 0.750]).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Model predictive accuracy was good when predictors were measured 2 to 4\u00a0weeks after primary care consultation, but poor when measured at the point of consultation. Future research will explore whether additional, nonmodifiable predictors improve point-of-consultation predictive performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Impact<\/jats:title>\n                    <jats:p>External validation demonstrated that these individualized prediction models were not sufficiently accurate to recommend their use in clinical practice. Further research is required to improve performance through inclusion of additional nonmodifiable risk factors.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ptj\/pzad128","type":"journal-article","created":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T12:57:56Z","timestamp":1695646676000},"source":"Crossref","is-referenced-by-count":4,"title":["Development and External Validation of Individualized Prediction Models for Pain Intensity Outcomes in Patients With Neck Pain, Low Back Pain, or Both in Primary Care Settings"],"prefix":"10.1093","volume":"103","author":[{"given":"Lucinda","family":"Archer","sequence":"first","affiliation":[{"name":"School of Medicine, Keele University , Keele, Staffordshire , UK"},{"name":"Institute for Applied Health Research, University of Birmingham , Birmingham , UK"},{"name":"National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre , 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