Abstract
Primary thyroid lymphoma (PTL) is such a rare malignancy that there are no large-scale prognostic proofs to create a consensus on optimal management. This study aimed to determine the survival outcomes of PTL and specify associated factors by building a prognostic nomogram and to analyze competing risks of death to balance the hazards and benefits of different therapeutic approaches. METHOD: A total of 1638 PTL patients from 2000 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Cox proportional hazard regression and competing risk analysis were applied. RESULTS: We have identified through Cox analysis that age in years, diffuse large B-cell lymphoma (DLBCL) pathology, lymph node dissection, radiation, and chemotherapy were independent prognostic factors for disease-specific survival (DSS). Based on these findings, we built a nomogram for predicting 5- and 10-year DSS and analyzed the overall survival (OS) by calculating cumulative incidence of death. The overall cumulative incidences of the 5- and 10-year PTL-specific cumulative death probabilities were 14.0% (95% CI: 12.3%-15.9%) and 16.3% (95% CI: 14.4%-18.4%), respectively, while the 5- and 10-year cumulative death probabilities from other causes were 12.4% (95% CI: 10.6%-12.3%) and 24.7% (95% CI: 22.1%-27.4%). Results from the competing risk hazards regression analysis revealed that older age and Ann Arbor grading were associated with a greater probability of death from other causes and death from PTL. Radioactive therapy by external beam radiation was associated with death from other causes only. DLBCL histology, lymph node dissection, and chemotherapy were correlated with death from PTL. Cumulative incidence curves demonstrated that the pathological type of lymphoma is the factor determining the likelihood of dying from PTL versus other causes. CONCLUSION: Patients' age, Ann Arbor stage, pathological type of lymphoma, and the use of specific therapy regimen should all be taken into consideration when devising individualized treatment strategies for PTL. Decision models based on our findings may help clinicians make better decisions by taking into account the competing risk of death from causes other than PTL.