Natural Language Processing of Radiology Reports to Assess Survival in Patients with Advanced Melanoma.

Background/

Objectives

To use natural language processing (NLP) to extract large-scale data from the CT radiology reports of patients with advanced melanoma treated with immunotherapy and to determine whether liver metastases affect survival.

Methods

Patient criteria (M1 disease subclassified into M1a, M1b, or M1c) as well as alternative criteria (M1 with advanced melanoma, imaged with CT chest, abdomen, and pelvis from July 2014-March 2019) were included retrospectively. NLP was used to identify metastases from CT reports, and then patients were classified according to American Joint Committee on Cancer (AJCC) staging disease subclassified into M1L+ or M1L-, indicating whether liver metastases were present or not). Statistical analysis included constructing Kaplan-Meier survival curves and calculating hazard ratios (HRs).

Results

2239 patients were included (mean age, 63 years). Whether using AJCC or alternative criteria, overall survival (OS) was poorest for M1L+ (entire cohort median OS, 0.69 years [95% CI: 0.60-0.82]; immunotherapy cohort median OS, 1.4 years [95% CI: 0.92-2.0]) compared to M1L- (entire cohort median OS, 1.8 years [95% CI: 1.4-2.2]; immunotherapy cohort median OS; M1L-, 2.9 years [95% CI: 2.3-3.9]). The median HR for M1L+ (median HR, 5.35 [95% CI: 4.59-6.24]) was higher than that for M0 (p < 0.001). The median HR for M1L+ (median HR, 2.13 [95% CI: 1.65-2.64]) was higher than that for M0 (p < 0.01).

Conclusions

Patients with advanced melanoma, particularly those with liver metastases, demonstrated inferior survival, even when treated with immunotherapy.