Risk prediction of intraoperative pain in percutaneous microwave ablation of lung tumors under CT guidance.

Abstract

To evaluate the effect of intraoperative pain in microwave ablation of lung tumors (MWALT) on local efficacy and establish the pain risk prediction model. It was a retrospectively study. Consecutive patients with MWALT from September 2017 to December 2020 were divided into mild and severe pain groups. Local efficacy was evaluated by comparing technical success, technical effectiveness, and local progression-free survival (LPFS) in two groups. All cases were randomly allocated into training and validation cohorts at a ratio of 7:3. A nomogram model was established using predictors identified by logistics regression in training dataset. The calibration curves, C-statistic, and decision curve analysis (DCA) were used to evaluate the accuracy, ability, and clinical value of the nomogram. A total of 263 patients (mild pain group: n = 126; severe pain group: n = 137) were included in the study. Technical success rate and technical effectiveness rate were 100% and 99.2% in the mild pain group and 98.5% and 97.8% in the severe pain group. LPFS rates at 12 and 24months were 97.6% and 87.6% in the mild pain group and 91.9% and 79.3% in the severe pain group (p = 0.034; HR: 1.90). The nomogram was established based on three predictors: depth of nodule, puncture depth, and multi-antenna. The prediction ability and accuracy were verified by C-statistic and calibration curve. DCA curve suggested the proposed prediction model was clinically useful. Severe intraoperative pain in MWALT reduced the local efficacy. An established prediction model could accurately predict severe pain and assist physicians in choosing a suitable anesthesia type. This study firstly provides a prediction model for the risk of severe intraoperative pain in MWALT. Physicians can choose a suitable anesthesia type based on pain risk, in order to improve patients' tolerance as well as local efficacy of MWALT. • The severe intraoperative pain in MWALT reduced the local efficacy. • Predictors of severe intraoperative pain in MWALT were the depth of nodule, puncture depth, and multi-antenna. • The prediction model established in this study can accurately predict the risk of severe pain in MWALT and assist physicians in choosing a suitable anesthesia type.