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Adjei, Ernest Kwasi

0000-0002-4004-3334

Mayo Clinic

Komfo Anokye Teaching Hospital

Citations 2

World Health Organization classification of tumours of the breast 6th edition 2026
Quinn, Cecily , Tan, Puay Hoon , Allison, Kimberly H. , Brogi, Edi , Lakhani, Sunil R. , Schnitt, Stuart J. , Fox, Stephen B. , Jaffer, Shabnam , Şahin, Ayşegül A. , Salgado, Roberto , Adjei, E, Helbich, Thomas H. , Sotiriou, C, Hodge, Jennelle C. , Khoury, Joseph D. , Puspanathan, Pavitratha, Giesen, Christine, Ruiz, Blanca Iciar Indave , Ellis, Ian, Lokuhetty, Dilani , Board, WCT Standing Editorial, Netto, George J. , Sahin, Aysegul , Sapino, Anna , Adjei, Ernest Kwasi , Geiersbach, Katherine , Helbich, Thomas H , Lambertini, Matteo , Sotiriou, Christos P. , Hodge, Jennelle C , Khoury, Joseph , Rekhi, Bharat , Ryska, Ales , Tse, Gary , Field, Andrew , Wijesinghe, Harshima , Puspanathan, Pavitratha , Giesen, Christine , Ruiz, Blanca Iciar Indave , Ellis, Ian , Lokuhetty, Dilani , Geiersbach, Katherine B. , Lambertini, Matteo , Field, Andrew , Ellis, Ian O. , board, WCT standing editorial

Histopathology | April 21, 2026 | Volume: 89 | Issue: 2 | Pages: 199-218

10.1111/his.70149 Get It

The 6th edition of the WHO Classification of Breast Tumours introduces both major and minor changes based on recent advances in our understanding of breast biology, developments in diagnostic modalities, identification of specific molecular targets and new treatment regimens necessitating modifications to pathology reporting and tumour biomarker categorisation. This review summarises the main changes that strive towards a classification of global relevance. In invasive carcinoma, predictive factors increasingly inform modern breast cancer treatment. The 6th edition provides an update on HER2 reporting categories following the DESTINY‐Breast 04 and 06 trials. Terminologies used to classify invasive tumours are clarified, with the term ‘variant’ now reserved for molecular/genetic alterations. Invasive lobular carcinoma (ILC) with extracellular mucin is recognised as a new diagnostic entity with prognostic implications. The diagnosis of mucinous carcinoma (MC) is reserved for mucin secreting carcinomas with grade 1 or 2 morphology and a favourable biomarker profile. The diagnosis of malignant phyllodes tumours requires only four of the original five adverse histological criteria. Classification of neuroendocrine tumours (NETs) is revised, recognising that the unified model, promoted in the 5th edition, is difficult to apply to the breast. New approaches to the classification of adenomyoepithelioma are discussed but the 5th edition system is broadly retained. A new section on ‘Small Diagnostic Samples’ outlines the merits of non‐operative biopsy diagnosis, the B coding system and the importance of multidisciplinary review. Changes to diagnostic practice and the emerging role of artificial intelligence, with advantages and challenges, are discussed in a new section on ‘Digital Pathology’.
Treatment patterns and outcomes of head and neck cancer in sub-Saharan Africa: Insights from a multi-institutional cancer dataset.
Addison, Eric, Apamo, Primus, Manirakiza, Achille , Mina, Syeda A. , Truman, Matt, Bogan, Aaron, Mongare, Ben Roger, Dibaba, Yonas, Mwango, Gladys , Kemper, Katherine E. , Fekadu, Adugna, Merrell, Kenneth W. , Osei‐Bonsu, Ernest , Falade, Ayo , Dodoo, Christopher , Adjei, Ernest Kwasi , Woldetsadik, Edom Seife

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: No page available

10.1200/jco.2025.43.16_suppl.e18017 Get It

e18017 Background: Head and neck (H&N) cancers affect the oral cavity, pharynx, larynx, salivary glands, nasal cavity, and sinuses. In Sub-Saharan Africa (SSA), the true burden of H&N cancers remains unclear, with available estimates suggesting approximately 47,000 new cases and 26,000 deaths annually. Limited cancer datasets hinder understanding of disease patterns and outcomes. This study explores patient characteristics, treatments, and outcomes to guide regional cancer control efforts. Methods: A cancer dataset was created and implemented at 4 leading teaching hospitals in Ghana, Kenya, Ethiopia, and Rwanda to systematically collect data on patient demographics, disease characteristics, and treatment patterns. Established through competitive grant funding, the primary objective of the database was to assess the indirect impact of the COVID-19 pandemic on cancer care. The dataset includes all cancer patients seen in consultation and/or treated between 2016 and 2023. In this study, a subset of patients diagnosed with H&N cancers was analyzed using descriptive statistics to assess clinical characteristics, treatments modalities, and patients' outcomes. Results: A total of 1,023 patients with H&N cancer were included in the analysis. The median age at diagnosis was 54 yrs (IQR 41-66), with 37% (n= 374) of the cohort being female. A total of 55% (n= 549) had no health insurance coverage. Of those with staging data, majority presented with advanced disease (89%) on presentation. Regarding treatment modality, 16% (n= 157) underwent surgery, 27% (n=279) received radiotherapy (RT), 14% (n= 143) received chemotherapy (CT), and 56% (n= 572) received no cancer therapy. Of those who received CT the timing was neoadjuvant (12%), concurrent with RT (22%), adjuvant after surgery (8.9%) or as palliative treatment (57%). Platinum-based agents (94%) were the most common CT, followed by Taxol-based (31%), and 5FU-based agents (27%). Regarding RT, planning was performed using 2D (55%) and 3D (45%) techniques. The median delivered dose was 60 Gy in 30 fractions. At a median follow up of 43 months, 1.6% were disease free, 10% (n= 103) were alive, 5.9% (n= 60) were confirmed dead, and 84% (n= 848) were lost to follow up. Conclusions: This study identifies key challenges in managing H&N cancers in SSA, including late-stage presentation, limited access to advanced treatment modalities, and a high lost to follow-up rate (84%). The reliance on older RT techniques such as 2D planning and the limited use of surgery highlight gaps in infrastructure and resource availability. Limited health insurance coverage suggests potential financial barriers to care and disparities in treatment access. Addressing these challenges will require greater investment in cancer care, expansion of the oncology workforce, and improvements in healthcare infrastructure to support better patient outcomes in the region.