Demographic and clinical profile of 1106 adult soft tissue sarcoma patients: A single institutional prospective database experience from India.

Abstract

Adult soft tissue sarcomas (STS) are rare and diverse. Current management is based on limited literature from the West. Therefore, data from different geographical regions is required, including the low-middle-income countries. This is our experience managing adult sarcomas in the tertiary cancer center of North India. This is a retrospective analysis of the structured sarcoma database of patients treated in the surgical oncology department between 1992 and 2020. The descriptive analysis includes demography, site distribution, diagnosis, histopathology variations, prior surgical interventions, and stage. A total of 1106 soft tissue sarcoma patients were treated in three decades. Age distribution was 13%, 43%, 31%, and 11% in <20, 21-40, and 41-60 and >60 years, respectively. The male-to-female ratio was 1.73. The anatomical distribution was 17%, 42%, 23%, 7%, 7%, and 3% in upper extremity, lower extremity, trunk, retroperitoneum, head and neck, and viscera, respectively. Overall, 49% of patients had undergone prior suboptimal surgeries at community hospitals. Common histology subtypes were synovial sarcoma (18%), undifferentiated pleomorphic sarcoma (UPS) (13%), dermatofibrosarcoma protuberans (12%), and liposarcoma (9%). A pathological discordance of 13% was identified between the initial and the final histologies. Overall, 61% of tumors were high-grade. Memorial Sloan Kettering Stages II and III were present in 33% and 35% of patients, respectively. This is one of the largest single institutional experiences of STS from the Asian population. Mostly young adults were affected with male preponderance. The lower extremity and trunk were common subsites. Frequent histologies were synovial sarcoma and UPS. A high rate of suboptimal surgical intervention at the community level and pathological discordance was noted. This study highlights the need to establish prospective structured databases for capturing quality information related to rare malignancies and providing insights for future research.