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- Title
Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma.
- Authors
Moore, Michael R.; Friesner, Isabel D.; Rizk, Emanuelle M.; Fullerton, Benjamin T.; Mondal, Manas; Trager, Megan H.; Mendelson, Karen; Chikeka, Ijeuru; Kurc, Tahsin; Gupta, Rajarsi; Rohr, Bethany R.; Robinson, Eric J.; Acs, Balazs; Chang, Rui; Kluger, Harriet; Taback, Bret; Geskin, Larisa J.; Horst, Basil; Gardner, Kevin; Niedt, George
- Abstract
Accurate prognostic biomarkers in early-stage melanoma are urgently needed to stratify patients for clinical trials of adjuvant therapy. We applied a previously developed open source deep learning algorithm to detect tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) images of early-stage melanomas. We tested whether automated digital (TIL) analysis (ADTA) improved accuracy of prediction of disease specific survival (DSS) based on current pathology standards. ADTA was applied to a training cohort (n = 80) and a cutoff value was defined based on a Receiver Operating Curve. ADTA was then applied to a validation cohort (n = 145) and the previously determined cutoff value was used to stratify high and low risk patients, as demonstrated by Kaplan–Meier analysis (p ≤ 0.001). Multivariable Cox proportional hazards analysis was performed using ADTA, depth, and ulceration as co-variables and showed that ADTA contributed to DSS prediction (HR: 4.18, CI 1.51–11.58, p = 0.006). ADTA provides an effective and attainable assessment of TILs and should be further evaluated in larger studies for inclusion in staging algorithms.
- Subjects
MELANOMA prognosis; BIOMARKERS; ADJUVANT treatment of cancer; CLINICAL trials; LYMPHOCYTES
- Publication
Scientific Reports, 2021, Vol 11, Issue 1, p1
- ISSN
2045-2322
- Publication type
Article
- DOI
10.1038/s41598-021-82305-1