Abstract P6-03-05: Clinico-pathological co-variates define a predictive model of breast cancer related lymphoedema (BCRL) in patients undergoing axillary surgery for breast cancer

Abstract Clinico-pathological co-variates define a predictive model of breast cancer related lymphoedema (BCRL) in patients undergoing axillary surgery for breast cancer CC Tang1*, J Timbres2*, KWD Ramsey1, A Mera2, S Irshad2, E Sawyer2, AA Khan1 1 Department of Plastic Surgery, The Royal Marsden Hospital, London, UK 2 School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, Guy’s Cancer Centre, King’s College London, London, UK. *These authors contributed equally Introduction Breast cancer-related lymphoedema (BCRL) negatively impacts body image, limb function and quality-of-life during cancer survivorship and affects 20% of women undergoing axillary clearance (ALND).1 Stratifying women undergoing axillary intervention into high- and low-risk groups for BCRL is important to identify those most likely to benefit from surgical interventions for lymphoedema prevention (eg LYMPHA) and mitigate BCRL risk in this subset of patients. In this study, we aimed to identify prognostic factors for lymphoedema incidence to develop a more accurate model of BCRL risk. Methods We performed a retrospective cohort study of breast cancer patients undergoing axillary surgery with (Ly+) and without (Ly-) subsequent lymphoedema. Controls were identified from the Breast Cancer Clinical Database, Guy’s and St Thomas’ Hospital NHS Foundation Trust (GSTT)) and diagnosed between 2000-2016, while cases were identified from the Lymphoedema Clinic at GSTT, diagnosed between 2000-2020. A multivariate logistic regression model was derived from univariate analyses using a stepwise, iterative process, confirmed with lasso regression, and evaluated within training and validation datasets to define a predictive risk score using methods described by Pavlou et al.2 Results 2040 patients (Ly+=541, Ly-=1499) who underwent axillary surgery (ALND = 1171, SLNB = 755) (were included in our analysis with a median follow up of 7.2 years (Ly+) and 9.8 years (Ly-). The final predictive model of BCRL risk contained variables for: mastectomy, grade, T-stage, N-stage, ER status, chemotherapy and radiotherapy. Here, specifically radiotherapy including a supraclavicular fossa field was associated with developing lymphoedema. The Hosmer–Lemeshow goodness-of-fit test showed the model to be well calibrated, and evaluation of the risk score using ROC curves showed good discrimination (AUC: 0.795). Lymphoedema was not found to negatively affect overall (unadjusted HR: 1.19 (95% CI: 0.92-1.53); p=0.178 and adjusted HR: 0.53 (95% CI: 0.38-0.73); p< 0.001) or disease free (unadjusted HR: 2.03 (95% CI: 1.59-2.61); p< 0.001 and adjusted HR: 0.92 (95% CI: 0.68-1.23); p=0.57) survival. Conclusion Our study identified clinico-pathological factors such as mastectomy, grade, T-stage, N-stage, ER status, chemo- and radiotherapy (specifically radiotherapy including a supraclavicular fossa field) to be predictive of developing BCRL following axillary surgery. Our model requires further validation but may have utility in stratifying patients for whom surgical strategies for lymphoedema prevention could be deployed to mitigate BCRL risk. References 1. DiSipio T, Rye S, Newman B, Hayes S. Incidence of unilateral arm lymphoedema after breast cancer: a systematic review and meta-analysis. Lancet Oncol. 2013 May;14(6):500-15. doi: 10.1016/S1470-2045(13)70076-7. Epub 2013 Mar 27. PMID: 23540561. 2. Pavlou M, Ambler G, Seaman S R, Guttmann O, Elliott P, King M et al. How to develop a more accurate risk prediction model when there are few events BMJ 2015; 351 :h3868 doi:10.1136/bmj.h3868 Citation Format: Chee Chee Tang, Jasmine Timbres, Kelvin Ramsey, Anca Mera, Sheeba Irshad, Elinor Sawyer, Aadil Khan. Clinico-pathological co-variates define a predictive model of breast cancer related lymphoedema (BCRL) in patients undergoing axillary surgery for breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-03-05.