Development of a Consensus-Based Risk Stratification Algorithm for HR+/HER2− Early Breast Cancer to Guide Adjuvant CDK4/6i Therapy: Outcomes from a Multidisciplinary Workshop in India

Krishna Mohan Mallavarapu,1,* Rakesh Reddy B,2,* Somashekhar SP,3,* Pankaj Goyal,4,* Vishwanath Sathyanarayanan,5 Amit Rauthan,6 Jyoti Bajpai,7 Prabhat Ghanshyam Bhargava,8 Mohit Agarwal,9 Rakesh Pinninti,1 Rachana Chennamaneni,10 Krishna Chaitanya P,11 Stalin Chowdary Bala,12 Venkateswar Rao Pydi,13 Ramavath Dev,14 PS Dattatreya,15 Ullas Batra,4 Govind Babu K,16 Disha Shetty,17 Kumardeep Paul,17 Priya Rathi,17 Maheboob Basade181Department of Medical Oncology, Basavatarakam Indo-American Cancer Institute and Research Center, Hyderabad, TG, India; 2Department of Medical Oncology, Apollo Hospitals, Visakhapatnam, AP, India; 3Department of Surgical and Gynecological Oncology, Aster CMI Hospital, Bangalore, KA, India; 4Department of Medical Oncology, Rajiv Gandhi Cancer Institute and Research Centre, Rohini, ND, India; 5Department of Medical Oncology, Apollo Hospitals, Bangalore, KA, India; 6Department of Medical Oncology, Immunotherapy and Precision Medicine, Manipal Hospital, Bangalore, KA, India; 7Department of Medical Oncology, Apollo Hospitals, Navi Mumbai, MH, India; 8Department of Medical Oncology, Tata Memorial Hospital, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, MH, India; 9Department of Medical Oncology, Fortis Hospital, Shalimar Bagh, ND, India; 10Department of Medical Oncology, Nizam’s Institute of Medical Sciences, Hyderabad, TG, India; 11Department of Medical Oncology, MNJ Institute of Oncology and Regional Cancer Centre, Hyderabad, TG, India; 12Department of Medical Oncology, Mahatma Gandhi Cancer Hospital and Research Institute, Visakhapatnam, AP, India; 13Department of Medical Oncology, Omega Cancer Hospitals, Visakhapatnam, AP, India; 14Department of Medical Oncology, KIMS Renova Cancer Institute, Visakhapatnam, AP, India; 15Department of Medical Oncology, KIMS Hospitals, Secunderabad, TG, India; 16Department of Medical Oncology, HCG Hospital, Bangalore, KA, India; 17Medical Affairs, Novartis Healthcare Private Limited, Mumbai, MH, India; 18Department of Medical Oncology, Jaslok Hospital and Research Centre, Mumbai, MH, India*These authors contributed equally to this workCorrespondence: Maheboob Basade, Department of Medical Oncology, Jaslok Hospital and Research Centre, Mumbai, MH, India, Email [email protected]: Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2–) early breast cancer (EBC) is treated with curative intent, but risk of recurrence (RoR) remains a challenge. The identification of high RoR EBC patients is inconsistent, highlighting the need for a simplified approach. This study aimed to develop an evidence-informed, consensus-based tool to support recurrence risk stratification and treatment decision-making in patients with HR+/HER2– EBC, incorporating multidisciplinary perspectives and evolving evidence from guidelines and trials.Methods: Five structured, multidisciplinary workshops were conducted across India, involving 135 experts, to integrate evidence and expert consensus into a practical algorithm for RoR assessment. The workshops included initial polling on clinical practices, followed by case-based discussions and literature review, with post-discussion polling used to capture shifts in expert perspectives.Results: Polling responses demonstrated consensus (defined as ≥ 70% agreement by experts) that all N1 patients are at a high RoR (94.3%) and that tumors ≥ 5 cm are associated with high risk (90.0%). Given that low-grade (G1) tumors are associated with a favorable prognosis (low risk) and high-grade (G3) tumors indicate a poorer prognosis (high risk), Ki-67–based treatment decision-making was considered most relevant for the moderate-grade (G2) subgroup. Accordingly, experts agreed that combining tumor grade G2 with Ki-67 assessment improves risk stratification in N0 patients with tumors < 5 cm (71.6%). A Ki-67 cut-off of ≥ 20% was considered critical (96.3%). The experts agreed that adjuvant cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) have an invasive disease-free survival (iDFS) advantage in all N1 (93.8%) and high risk N0 (91.1%) patients with HR+/HER2− EBC.Conclusion: The developed algorithm provides a user-friendly framework to facilitate uniform risk stratification and optimize HR+/HER2– EBC treatment in India. Further prospective and real-world validation is required to establish its clinical utility and evaluate its impact on treatment decisions.Keywords: early breast cancer, risk of recurrence, prognostic factors, risk assessment, algorithm, CDK4/6i