A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study. Issue 9 (September 2022)

• Record Type: Journal Article
• Authors: Kleppe, Andreas; Skrede, Ole-Johan; De Raedt, Sepp; Hveem, Tarjei S; Askautrud, Hanne A; Jacobsen, Jørn E; Church, David N; Nesbakken, Arild; Shepherd, Neil A; Novelli, Marco; Kerr, Rachel; Liestøl, Knut; Kerr, David J; Danielsen, Håvard E
• Is Part Of: Lancet oncology. Volume 23:Issue 9(2022)
• Page Start: 1221
• Page End: 1232
• Publication Date: 2022-09
• Subjects: Oncology -- Periodicals; Neoplasms -- Periodicals; Cancérologie -- Périodiques; Oncologie; Oncology; Periodicals; Electronic journals; 616.994005
• DOI: 10.1016/S1470-2045(22)00391-6
• Languages: English
• ISSNs: 1470-2045

Abstract

Summary: Background: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and was observed to outperform established molecular and morphological markers of patient outcome after primary colorectal cancer resection. The aim of the present study was to develop a clinical decision support system based on DoMore-v1-CRC and pathological staging markers to facilitate individualised selection of adjuvant treatment. Methods: We estimated cancer-specific survival in subgroups formed by pathological tumour stage (pT<4 or pT4), pathological nodal stage (pN0, pN1, or pN2), number of lymph nodes sampled (≤12 or >12) if not pN2, and DoMore-v1-CRC classification (good, uncertain, or poor prognosis) in 997 patients with stage II or III colorectal cancer considered to have no residual tumour (R0) from two community-based cohorts in Norway and the UK, and used these data to define three risk groups. An external cohort of 1075 patients with stage II or III R0 colorectal cancer from the QUASAR 2 trial was used for validation; these patients were treated with single-agent capecitabine. The proposed risk stratification system was evaluated using Cox regression analysis. We similarly evaluated a risk stratification system intended to reflect current guidelines and clinical practice. The primary outcome was cancer-specific survival. Findings: The new risk stratification system provided a hazard ratio of 10·71 (95% CI 6·39–17·93; p<0·0001) for high-risk versus low-risk patients and 3·06 (1·73–5·42; p=0·0001) for intermediate versus low risk in the primary analysis of the validation cohort. Estimated 3-year cancer-specific survival was 97·2% (95% CI 95·1–98·4; n=445 [41%]) for the low-risk group, 94·8% (91·7–96·7; n=339 [32%]) for the intermediate-risk group, and 77·6% (72·1–82·1; n=291 [27%]) for the high-risk group. The guideline-based risk grouping was observed to be less prognostic and informative (the low-risk group comprised only 142 [13%] of the 1075 patients). Interpretation: Integrating DoMore-v1-CRC and pathological staging markers provided a clinical decision support system that risk stratifies more accurately than its constituent elements, and identifies substantially more patients with stage II and III colorectal cancer with similarly good prognosis as the low-risk group in current guidelines. Avoiding adjuvant chemotherapy in these patients might be safe, and could reduce morbidity, mortality, and treatment costs. Funding: The Research Council of Norway.