Olufunmilayo I Olopade | Search PubMed

PubMed2026

The African Cancer Leaders Institute: a decade of strategic development of the African next generation leaders in cancer care, research, education and advocacy.

Leadership and mentorship play an important role in supporting the career development of health professionals. In many African countries, supervision activities focus on technical and operational aspects rather than catalysing career and leadership development. Thus, mentorship and coaching interventions need to be implemented in African healthcare institutions as components of health systems strengthening strategies. Due to its holistic nature, cancer care involves interprofessional collaborations to develop and provide a problem-solving mindset. It is therefore an area that would benefit from leadership and mentorship, mainly in a limited-resources context. The identified benefits from leadership development in cancer care in Africa led to the creation of the African Cancer Leaders Institute (ACLI) of the African Organization for Research and Training in Cancer (AORTIC), consisting of mentors and trainees from Africa and the USA. ACLI trainees are selected through a competitive application process. During the ACLI biennial meetings, coinciding with the AORTIC conference, trainees, including early-stage/mid-career investigators, oncologists, nurses, advocates and other health professionals, meet to learn about best practices in cancer research, grant writing, scientific reporting, mentor relationships, academic pressures and professional-personal life balance. This paper describes the goals of the ACLI, its mission and achievements, the vision behind creating such important programmes and the benefits of its participants in leadership, coaching and mentorship in improving cancer care in Africa.

Humans↗

PubMed2026

Development and Validation of a Multimodal Clinical, Pathologic, and Genomic Model for Breast Cancer Recurrence.

PURPOSE: To develop and validate a multimodal recurrence-risk model integrating histology, genomic testing, and clinical variables. METHODS: We developed AI-Path, a whole-slide image biomarker for recurrence prediction trained in CALGB 9344, and validated it in three independent cohorts: TAILORx, a multi-site Chicago cohort, and the MDX-BRCA cohort. We then integrated AI-Path with Oncotype DX Recurrence Score (RS), tumor size, and nodal status into a Cox model, PathClinRS, fit using 60% of cases from TAILORx, with the remaining 40% held out for validation. The primary end point was distant recurrence-free interval. Performance was assessed using Harrell's concordance index (C-index) and Kaplan-Meier analyses. RESULTS: A total of 12,418 patients were included. In TAILORx, AI-Path outperformed RS for distant recurrence (C-index, 0.682 vs 0.647; P = .038), driven by superior prediction of late recurrence (0.656 vs 0.567; P < .001). In node-negative disease, PathClinRS outperformed RSClin in the TAILORx fitting (0.72 vs 0.70; P = .016) and validation sets (0.74 vs 0.70; P = .004). In node-positive disease, PathClinRS outperformed RSClinN+ in Chicago (0.94 vs 0.74; P < .001) and MDX-BRCA (0.71 vs 0.66; P = .004) cohorts. Compared with NATALEE eligibility, PathClinRS identified nearly twice as many high-risk node-negative patients while maintaining a comparable 10-year distant recurrence risk (16.7% vs 16.6% per NATALEE eligibility in TAILORx fitting; 21.0% vs 19.4% in TAILORx validation). PathClinRS identified 68% of intermediate risk premenopausal patients as low-risk with no evidence of chemotherapy benefit, compared to only 36% identified as low risk by standard clinicopathologic criteria. CONCLUSION: Digital histopathology provides prognostic information complementary to genomic assays and has the potential to personalize therapy beyond existing clinicogenomic tools.

Journal Article↗