Clinical and pathologic predictors of survival in patients with thymoma

Abstract

Objective: To evaluate the Johns Hopkins Hospital experience with 136 thymomas over the past 40 years. This number of patients allowed quantitative estimation of the independent influence of common clinicopathologic risk factors using multivariate analysis.

Summary background data: Thymomas vary widely in terms of recurrence and influence on overall survival. Several series have indicated the importance of initial tumor invasion, as well as the extent of surgical resection, as predictors of recurrence and survival after thymoma resection. However, findings have been equivocal when other predictors of prognosis were examined.

Methods: The authors evaluated 136 patients seen at the Johns Hopkins Hospital between 1957 and 1997 with a pathologic diagnosis of thymoma. Demographic information, clinical staging data, surgical and adjuvant treatment details, and patient follow-up data were obtained from the patient record and from detailed patient or family interviews. Microscopic sections of all 136 patients were reviewed by two pathologists blinded to the clinical data. All data were analyzed by multivariate Cox regression analysis, which allowed the quantification of the independent predictive value of 12 putative clinicopathologic prognostic indicators.

Results: Completeness of follow-up was 99%, 99%, and 98% of eligible patients at 5, 10, and 15 years, respectively. Forty percent of the patients had associated myasthenia gravis and 27% had a secondary primary malignancy. Overall patient survival rates were 71%, 56%, 44%, 38%, and 33% at 5, 10, 15, 20, and 25 years, respectively. Overall, the thymoma-related mortality rate was 14%; the nonthymoma-related mortality rate was 26%. Incomplete resection, preoperative absence of myasthenia gravis, and advanced Lattes/Bernatz pathologic class were found to be independent predictors of poorer overall survival.

Conclusions: These findings support a policy of aggressive, complete surgical resection of all thymomas when feasible. Thymoma behaves as a rather indolent tumor, with most deaths from causes unrelated to thymoma or its direct treatment. Clinicians should have an increased awareness of the possibility of second primary malignancies in patients with thymoma.

Figure 1. Overall and thymoma-specific Kaplan-Meier survival of 136 thymoma patients. The median overall survival was 12 years. Here, the Kaplan-Meier curve for thymoma-specific survival is shown for comparison. Note that thymoma-specific survival greatly exceeds overall survival.

Figure 2. Influence of clinical stage on overall survival. (A) Masaoka stage is a significant prognostic predictor of survival, as evaluated by log-rank analysis (p < 0.003). (B) The discrimination between benign (stage I) and malignant (stages II to IV) disease appeared to be optimal when the Masaoka stages were grouped. However, when Masaoka stage was evaluated by Cox regression, it failed to be a significant independent predictor of overall survival.

Figure 3. Effect of the extent of surgical resection on survival. (A) Complete resection is a significant prognostic predictor of overall survival, as evaluated by log-rank analysis. (B) Complete resection is a significant prognostic indicator of survival from thymoma, as evaluated by log-rank analysis. Complete resection is the most important independent predictor of overall survival and the only independent predictor of thymoma-related survival, as analyzed by Cox regression.

Figure 4. The effect of L/B pathologic classification on overall survival. (A) By log-rank analysis, L/B classification predicts prognosis, with spindle, lymphocytic, and mixed thymomas being associated with fewer overall deaths (p < 0.001). (B) Through selective grouping, the overall differences in survival are emphasized. Indeed, L/B pathologic classification did prove to be an independent predictor of overall survival by Cox regression.

Figure 5. The effect of Müller-Hermelink pathologic grade on overall survival. (A) By log-rank analysis, substantial differences in overall survival as a function of Müller-Hermelink pathologic grade are apparent (p < 0.02). (B) By subsequent grouping of the pathologic grades, the importance of Müller-Hermelink pathologic grade is emphasized. However, Cox regression analysis failed to find Müller-Hermelink grade to be an independent predictor of overall survival.

Figure 6. The presence of preoperative MG had a strikingly positive prognostic effect on overall survival. Multivariate analysis by the Cox regression model also confirmed preoperative MG as an independent predictor of overall survival.