A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer
Background: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). Methods: 1330 patients with ES-NSCLC were acquired from 3 independent sources and di...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-07-01
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| Series: | EBioMedicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352396421002747 |
| _version_ | 1818591546835992576 |
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| author | Xiangxue Wang Kaustav Bera Cristian Barrera Yu Zhou Cheng Lu Pranjal Vaidya Pingfu Fu Michael Yang Ralph Alexander Schmid Sabina Berezowska Humberto Choi Vamsidhar Velcheti Anant Madabhushi |
| author_facet | Xiangxue Wang Kaustav Bera Cristian Barrera Yu Zhou Cheng Lu Pranjal Vaidya Pingfu Fu Michael Yang Ralph Alexander Schmid Sabina Berezowska Humberto Choi Vamsidhar Velcheti Anant Madabhushi |
| author_sort | Xiangxue Wang |
| collection | DOAJ |
| description | Background: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). Methods: 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. Findings: CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D3 (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR = 1.41, adj. P < .001) and D3 (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR = 0.42, adj. P = .006) and D3 (HR = 0.46, adj. P = .08). Interpretation: CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients. |
| first_indexed | 2024-12-16T10:14:10Z |
| format | Article |
| id | doaj.art-e5a09d38255e45c88fe57738e7605aef |
| institution | Directory Open Access Journal |
| issn | 2352-3964 |
| language | English |
| last_indexed | 2024-12-16T10:14:10Z |
| publishDate | 2021-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EBioMedicine |
| spelling | doaj.art-e5a09d38255e45c88fe57738e7605aef2022-12-21T22:35:30ZengElsevierEBioMedicine2352-39642021-07-0169103481A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancerXiangxue Wang0Kaustav Bera1Cristian Barrera2Yu Zhou3Cheng Lu4Pranjal Vaidya5Pingfu Fu6Michael Yang7Ralph Alexander Schmid8Sabina Berezowska9Humberto Choi10Vamsidhar Velcheti11Anant Madabhushi12Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USACenter for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USACenter for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USACenter for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USACenter for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USACenter for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USADepartment of Population and Quantitative Health Sciences, Case Western Reserve University, OH, USADepartment of Pathology-Anatomic, University Hospitals, OH, USADivision of General Thoracic Surgery, University Hospital Berne, Bern, SwitzerlandInstitute of Pathology, University of Bern, Bern, Switzerland; Department of Laboratory Medicine and Pathology, Institute of Pathology, Lausanne University Hospital and Lausanne University, Lausanne, SwitzerlandDepartment of Pulmonary and Critical Care Medicine, Respiratory Institute, Cleveland Clinic Foundation, OH, USADepartment of Hematology and Oncology, NYU Langone Health, NY, USACenter for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA; Corresponding author at: Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, OH, USA.Background: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). Methods: 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. Findings: CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D3 (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR = 1.41, adj. P < .001) and D3 (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR = 0.42, adj. P = .006) and D3 (HR = 0.46, adj. P = .08). Interpretation: CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients.http://www.sciencedirect.com/science/article/pii/S2352396421002747Early-stage non-small cell lung cancerComputational pathologyPrognostic and predictive |
| spellingShingle | Xiangxue Wang Kaustav Bera Cristian Barrera Yu Zhou Cheng Lu Pranjal Vaidya Pingfu Fu Michael Yang Ralph Alexander Schmid Sabina Berezowska Humberto Choi Vamsidhar Velcheti Anant Madabhushi A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer EBioMedicine Early-stage non-small cell lung cancer Computational pathology Prognostic and predictive |
| title | A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer |
| title_full | A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer |
| title_fullStr | A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer |
| title_full_unstemmed | A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer |
| title_short | A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer |
| title_sort | prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non small cell lung cancer |
| topic | Early-stage non-small cell lung cancer Computational pathology Prognostic and predictive |
| url | http://www.sciencedirect.com/science/article/pii/S2352396421002747 |
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