TY - JOUR
T1 - Development and validation of prediction models for health-related quality of life outcomes after breast cancer surgery and reconstruction
AU - Verheul, Elfi M.
AU - Karsten, Maria Margarete
AU - Gebert, Pimrapat
AU - Doppelbauer, Lea
AU - Borstnar, Simona
AU - Siesling, Sabine
AU - Lingsma, Hester F.
AU - Vrancken-Peeters, Noëlle J.M.C.
AU - Stiggelbout, Anne M.
AU - Mureau, Marc A.M.
AU - Koppert, Linetta B.
AU - van Klaveren, David
AU - Bak, Marieke
AU - de Wreede, Liesbeth C.
AU - Frank, Kasper
AU - Hartman, Laura
AU - Hedayati, Elham
AU - Hackmann, Toby
AU - Hallsson, Lára R.
AU - Engelberts, Yassin
AU - Liu, Yufeng
AU - Lal, Daisy Monika
AU - Korfage, Ida J.
AU - Nwosu, Amara Callistus
AU - Oliveira, Claudia Cruz
AU - Perić, Barbara
AU - Pazo-Cid, Roberto
AU - Romero-Piqueras, Carlos
AU - Rietjens, Judith
AU - Snelders, Dirk
AU - Siebert, Uwe
AU - Sroczynski, Gaby
AU - Steyerberg, Ewout
AU - van Mulligen, Erik
AU - Wit, Tamara
AU - Wouters, Michel W.
N1 - Publisher Copyright:
© 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/
PY - 2026/4
Y1 - 2026/4
N2 - BackgroundPredictions of Health-Related Quality of Life (HRQoL) outcomes could support realistic recovery expectations after breast cancer (BC) surgery. We aimed to develop and validate prediction models for HRQoL outcomes after BC surgery.MethodsWe used three datasets of BC patients from Berlin, Germany; Ljubljana, Slovenia; and Rotterdam; Netherlands. We included non-metastasised patients who were surgically treated for an initial diagnosis of BC and completed pre- and postoperative validated questionnaires. We used linear mixed models to analyse 15 domains of the EORTC QLQ-C30 and EORTC QLQ-BR23 over a two-year horizon. Baseline domain score (measured pre-operatively), age, BMI, smoking, TN stage, receptor status, neoadjuvant chemotherapy, axillary surgery and surgery type (breast-conserving, mastectomy, and immediate implant-based reconstruction) were included as predictors. Predictive performance at validation was assessed by the proportion of variance explained (marginal R2; mR2).ResultsWe included N = 795 patients from Germany for development and N = 623 from Slovenia and N = 417 from Netherlands for validation. The largest proportion of variance was explained by the prediction models for sexual functioning (SF, mR2 35%), physical functioning (PF, mR2 29%), body image (BI, mR2 26%), and cognitive functioning (CF, mR2 25%). The models captured meaningfully different trends over time for different outcomes and surgery types. The predictive performance of the models was largely driven by the baseline domain score. Performance was reasonable at external validation, with r2 values of 19–33% for PF, 10–17% for CF, 15–18% for BI, and 22–28% for SF, although some other outcomes (e.g. breast symptoms and role functioning) showed miscalibration, indicating a need for recalibration.ConclusionHRQoL after breast cancer surgery can be predicted using simple models with baseline domain scores and surgery type, demonstrating a new opportunity for Patient-Reported Outcome Measures (PROMs) in personalized care.
AB - BackgroundPredictions of Health-Related Quality of Life (HRQoL) outcomes could support realistic recovery expectations after breast cancer (BC) surgery. We aimed to develop and validate prediction models for HRQoL outcomes after BC surgery.MethodsWe used three datasets of BC patients from Berlin, Germany; Ljubljana, Slovenia; and Rotterdam; Netherlands. We included non-metastasised patients who were surgically treated for an initial diagnosis of BC and completed pre- and postoperative validated questionnaires. We used linear mixed models to analyse 15 domains of the EORTC QLQ-C30 and EORTC QLQ-BR23 over a two-year horizon. Baseline domain score (measured pre-operatively), age, BMI, smoking, TN stage, receptor status, neoadjuvant chemotherapy, axillary surgery and surgery type (breast-conserving, mastectomy, and immediate implant-based reconstruction) were included as predictors. Predictive performance at validation was assessed by the proportion of variance explained (marginal R2; mR2).ResultsWe included N = 795 patients from Germany for development and N = 623 from Slovenia and N = 417 from Netherlands for validation. The largest proportion of variance was explained by the prediction models for sexual functioning (SF, mR2 35%), physical functioning (PF, mR2 29%), body image (BI, mR2 26%), and cognitive functioning (CF, mR2 25%). The models captured meaningfully different trends over time for different outcomes and surgery types. The predictive performance of the models was largely driven by the baseline domain score. Performance was reasonable at external validation, with r2 values of 19–33% for PF, 10–17% for CF, 15–18% for BI, and 22–28% for SF, although some other outcomes (e.g. breast symptoms and role functioning) showed miscalibration, indicating a need for recalibration.ConclusionHRQoL after breast cancer surgery can be predicted using simple models with baseline domain scores and surgery type, demonstrating a new opportunity for Patient-Reported Outcome Measures (PROMs) in personalized care.
KW - Breast cancer surgery
KW - Health-related quality of life (HRQoL)
KW - Patient-centered care
KW - Patient-reported outcome measures (PROMs)
KW - Prediction model
UR - https://www.scopus.com/pages/publications/105034594036
U2 - 10.1016/j.ejso.2026.111466
DO - 10.1016/j.ejso.2026.111466
M3 - Article
C2 - 41689947
AN - SCOPUS:105034594036
SN - 0748-7983
VL - 52
JO - European Journal of Surgical Oncology
JF - European Journal of Surgical Oncology
IS - 4
M1 - 111466
ER -