{
  "abstract": "Background This study aimed to identify clinical factors and develop a predictive model for pathologic complete response (pCR) and major pathologic response (MPR) in non-small cell lung cancer (NSCLC) patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors (ICIs).Methods Cases meeting inclusion criteria were divided into high- and low-risk groups according to 75 clinical indicators based on 10-fold LASSO selection. Logistic regression was employed to analyze both pCR and MPR. The accuracy of the nomograms was assessed using the time-dependent area under the curve (AUC).Results A total of 883 patients from four multiple centers were included in the study, with 526 assigned to the training set and 357 to the testing set ( figure 1). The AUC was determined for the prediction of pCR (training: 0.97; testing: 0.87) and MPR (training: 0.94; testing: 0.85). Significant associations were observed between the preoperative tumor maximum diameter, preoperative tumor maximum standardized uptake value (SUVmax), changes in tumor SUVmax, percentage of tumor reduction, baseline total CYFRA21-1 and pathological response (P < 0.001).Conclusions The combined application of clinical indicators including non-invasive tumor imaging and hematology can help clinicians to obtain a higher ability to predict NSCLC patient’s pathological remission, and the effect is better than that of clinical factors alone. These findings could help guide personalized treatment strategies in this patient population.Consent Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.Ethics Approval The use of patients‘ information was approved by the Ethics Committee of the Tianjin Medical University Cancer Institute and Hospital (Approve number: bc2022323).Abstract 109 Figure 1Graphic abstract. Flow chart of our study",
  "authors": [
    {
      "affiliations": [
        "Tianjin Medical University Cancer Institute and Hospital, Tianjin, China"
      ],
      "name": "Mengzhe Zhang"
    },
    {
      "affiliations": [
        "Tianjin Medical University Cancer Institute and Hospital, Tianjin, China"
      ],
      "name": "Zhenfa Zhang"
    }
  ],
  "title": "109 Multicenter exploration of clinical, imaging, and immunological predictors for pCR and MPR in NSCLC neoadjuvant chemoimmunotherapy",
  "uid": "dabb315b-1504-55c0-98ae-9262ad68a98c"
}