PMID- 36388789 OWN - NLM STAT- PubMed-not-MEDLINE LR - 20221119 IS - 2305-5839 (Print) IS - 2305-5847 (Electronic) IS - 2305-5839 (Linking) VI - 10 IP - 20 DP - 2022 Oct TI - Development and validation of a model to predict the risk of recurrence in patients with laryngeal squamous cell carcinoma after total laryngectomy. PG - 1118 LID - 10.21037/atm-22-4802 [doi] LID - 1118 AB - BACKGROUND: Recurrence is still the main obstacle to the survival of laryngeal squamous cell carcinoma (LSCC) patients who have undergone a total laryngectomy. Previous models for recurrence prediction in patients with LSCC were based on pathological information, while the role of easily accessible inflammatory markers in the prognosis of LSCC patients has rarely been reported. This study sought to develop and validate a model to predict the risk of recurrence in LSCC patients who underwent total laryngectomy. METHODS: A total of 204 LSCC patients who underwent a total laryngectomy were included in this retrospective cohort study. Demographics, pathology, and inflammatory markers of patients were collected. All the patients were randomly divided into a training set and a test set at a ratio of 4:1. Patients were followed up for 3 years after surgery or until death occurred during this period. The random-forest method was used to develop a predictive model. The performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC) with the 95% confidence interval (CI), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: Of the 204 LSCC patients, 56 (27.45%) patients had a recurrence. The random-forest prediction model was an all-factor model, and the most important predictors of the model were the albumin/globulin ratio (AGR), neutrophil/lymphocyte ratio (NLR), and platelet/lymphocyte ratio (PLR), with proportions of 0.121, 0.100, and 0.092, respectively. The AUCs of the model in predicting the recurrence of LSCC in the training set and the test set were 0.960 (95% CI, 0.931-0.989) and 0.721 (95% CI, 0.716-0.726), respectively. The sensitivity, specificity, accuracy, PPV, and NPV of the model in the test set were 0.750 (95% CI, 0.505-0.995), 0.690 (95% CI, 0.521-0.858), 0.707 (95% CI, 0.568-0.847), 0.500 (95% CI, 0.269-0.921), and 0.870 (95% CI, 0.732-1.000), respectively. CONCLUSIONS: A model to predict the risk of recurrence in LSCC patients who have undergone a total laryngectomy was established, and inflammatory markers AGR, NLR, and PLR play an important role in the predictive model. CI - 2022 Annals of Translational Medicine. All rights reserved. FAU - Wang, Dapeng AU - Wang D AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Guo, Ruyuan AU - Guo R AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Luo, Ning AU - Luo N AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Ren, Xiaolu AU - Ren X AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Asarkar, Ameya A AU - Asarkar AA AD - Department of Otolaryngology/Head and Neck Surgery, LSU Health, Shreveport, LA, USA. FAU - Jia, Haixia AU - Jia H AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Yang, Fang AU - Yang F AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Ren, Shuhui AU - Ren S AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. FAU - Lu, Ping AU - Lu P AD - Department of Radiation Oncology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. LA - eng PT - Journal Article PL - China TA - Ann Transl Med JT - Annals of translational medicine JID - 101617978 PMC - PMC9652542 OTO - NOTNLM OT - Laryngeal squamous cell carcinoma (LSCC) OT - prediction model OT - recurrence OT - total laryngectomy COIS- Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-22-4802/coif). The authors have no conflicts of interest to declare. EDAT- 2022/11/18 06:00 MHDA- 2022/11/18 06:01 PMCR- 2022/10/01 CRDT- 2022/11/17 12:17 PHST- 2022/07/28 00:00 [received] PHST- 2022/10/14 00:00 [accepted] PHST- 2022/11/17 12:17 [entrez] PHST- 2022/11/18 06:00 [pubmed] PHST- 2022/11/18 06:01 [medline] PHST- 2022/10/01 00:00 [pmc-release] AID - atm-10-20-1118 [pii] AID - 10.21037/atm-22-4802 [doi] PST - ppublish SO - Ann Transl Med. 2022 Oct;10(20):1118. doi: 10.21037/atm-22-4802.