| Objective:This study was designed to investigate the incidence, clinical features and progression-free survival(PFS) of patients with cavitating lung cancer. Choose the best response evaluation criteria on lung cancer with certain radiographic signs by comparing the competency to predict PFS of patients between modified methods with version 1.1 Response Evaluation Criteria in Solid Tumors(RECIST1.1). Methods:1. We retrospectively investigated the incidence, clinical features and progression-free survival of patients with tumor cavitation among 947 lung cancer patients. Distribution of disease variables was analyzed using the chi-squared test. The significant variables were analyzed by conditional Logistic regression analysis. Survival curves were constructed with the Kaplan-Meier product limit method and compared using the logrank test. Multiple factors analysis was made using Cox’s proportional hazards regression model.2. 105 patients with certain radiographic signs were identified based on inclusion criteria. Besides RECIST1.1, we use the modified methods to evaluate their efficacy. Log rank test is also used to compare the PFS of patients with different response evaluated by four method. Results:1. The proportion of cases with basic cavitation is 5.4%, in non-small cell lung cancer(NSCLC) is 7.0%, in squamous cell carcinoma of lung is 11.1%, in adenocarcinoma of lung is 3.4%, and in small cell lung cancer(SCLC) is 1.1%. The patients who are more prone to have baseline cavitation, have some characteristic as follows, age beyond 60 and with a history of diabetes, drinking, squamous cell carcinomas, peripheral lung cancer, the longest diameter of tumor of 5-7cm and distant metastasis. The incidences of cavitation after treatment in overall lung cancer, NSCLC, squamous cell carcinoma, adenocarcinoma and SCLC are 2.6%, 3.0%, 4.9%, 1.8%, 1.6%, respectively. Male, squamous cell carcinomas, the longest diameter of tumor beyond 7cm are associated with occurrence of post-therapeutic cavitation, the treatment is related factor too.2. Baseline cavitation associates with longer PFS and, Cyfra21-1 is an independent predictor of PFS. Tumor cavitation after treatment associates with shorter PFS and, smoking history is an independent predictor on PFS, treatment also has influence on PFS. In patients with basic cavitation, RECIST1.1 scores accurately predicted differences in PFS(p = 0.076) whereas mRECIST evaluation of tumor response did not predict PFS differences(p = 0.550). However, in the subset of patients with post-therapeutic cavitation in evaluation by mRECIST in patients with post-therapeutic cavitation, there was a significant difference between PFS of patients with different responses(p = 0.004) but no significant difference in PFS in using RECIST1.1(p = 0.477). In patients with only tumor density changes there were no significant difference in PFS when either RECIST1.1 or density criteria was used to assess tumor response(p = 0.419). In patients with a change in size along the tumor’s short axis of tumor, short axis criteria could predict significant difference in PFS(p =0.004). Conclusion: 1. Both patients with baseline and post-therapeutic cavitation presented special clinical features and progression-free survival, PFS of patients with baseline cavitation is longer than the cases without it. PFS of patients with post-therapeutic cavitation is shorter than the patients without it. 2. RECIST1.1 provides the best assessment of tumor response and best predicts PFS for patients with basic cavitation. m RECIST provided better PFS prognostic information than RECIST1.1 in patients with post-therapeutic cavitation and short axis criteria provides better PFS prognostic information than RECIST1.1 in patients with changes in the short axis of tumor diameter. Changes in tumor density were not a useful prognostic sign. after treatment was not a useful predictor of PFS. |
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