Evidence map›Paper›PMID 42764958›Full record

ArticleBreast cancer (Dove Medical Press)2026

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, Rakesh Reddy B, Somashekhar Sp, Pankaj Goyal, Vishwanath Sathyanarayanan, Amit Rauthan, Jyoti Bajpai, Prabhat Ghanshyam Bhargava, Mohit Agarwal, Rakesh Pinninti and 12 more

Abstract read
In one paragraph

Article in Breast cancer (Dove Medical Press), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Krishna Mohan Mallavarapu *Department of Medical Oncology, Basavatarakam Indo-American Cancer Institute and Research Center, Hyderabad, TG, India.
Rakesh Reddy B *Department of Medical Oncology, Apollo Hospitals, Visakhapatnam, AP, India.
Somashekhar Sp *Department of Surgical and Gynecological Oncology, Aster CMI Hospital, Bangalore, KA, India.ORCID 0000-0002-7898-1625
Pankaj Goyal *Department of Medical Oncology, Rajiv Gandhi Cancer Institute and Research Centre, Rohini, ND, India.
Vishwanath SathyanarayananDepartment of Medical Oncology, Apollo Hospitals, Bangalore, KA, India.
Amit RauthanDepartment of Medical Oncology, Immunotherapy and Precision Medicine, Manipal Hospital, Bangalore, KA, India.
Jyoti BajpaiDepartment of Medical Oncology, Apollo Hospitals, Navi Mumbai, MH, India.
Prabhat Ghanshyam BhargavaDepartment of Medical Oncology, Tata Memorial Hospital, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, MH, India.
Mohit AgarwalDepartment of Medical Oncology, Fortis Hospital, Shalimar Bagh, ND, India.
Rakesh PinnintiDepartment of Medical Oncology, Basavatarakam Indo-American Cancer Institute and Research Center, Hyderabad, TG, India.ORCID 0009-0007-9412-6155
Rachana ChennamaneniDepartment of Medical Oncology, Nizam's Institute of Medical Sciences, Hyderabad, TG, India.
Krishna Chaitanya PDepartment of Medical Oncology, MNJ Institute of Oncology and Regional Cancer Centre, Hyderabad, TG, India.
Stalin Chowdary BalaDepartment of Medical Oncology, Mahatma Gandhi Cancer Hospital and Research Institute, Visakhapatnam, AP, India.
Venkateswar Rao PydiDepartment of Medical Oncology, Omega Cancer Hospitals, Visakhapatnam, AP, India.
Ramavath DevDepartment of Medical Oncology, KIMS Renova Cancer Institute, Visakhapatnam, AP, India.
P S DattatreyaDepartment of Medical Oncology, KIMS Hospitals, Secunderabad, TG, India.
Ullas BatraDepartment of Medical Oncology, Rajiv Gandhi Cancer Institute and Research Centre, Rohini, ND, India.ORCID 0000-0003-3306-9824
Govind Babu KDepartment of Medical Oncology, HCG Hospital, Bangalore, KA, India.
Disha ShettyMedical Affairs, Novartis Healthcare Private Limited, Mumbai, MH, India.
Kumardeep PaulMedical Affairs, Novartis Healthcare Private Limited, Mumbai, MH, India.
Priya RathiMedical Affairs, Novartis Healthcare Private Limited, Mumbai, MH, India.
Maheboob BasadeDepartment of Medical Oncology, Jaslok Hospital and Research Centre, Mumbai, MH, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: 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.

Indexed as

algorithmCDK4/6iearly breast cancerprognostic factorsrisk assessmentrisk of recurrence

Identifiers

PMID42764958
PMCPMC13589968

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.