A novel nomogram for predicting overall survival in patients with tongue squamous cell carcinoma using clinical features and MRI radiomics data: a pilot study.

OBJECTIVE: Tongue squamous cell carcinoma (TSCC) accounts for 43.4% of oral cancers in China and has a poor prognosis. This study aimed to explore whether radiomics features extracted from preoperative magnetic resonance imaging (MRI) could predict overall survival (OS) in patients with TSCC. METHODS: The clinical imaging data of 232 patients with pathologically confirmed TSCC at Xiangyang No. 1 People's Hospital were retrospectively analyzed from February 2010 to October 2022. Based on 2-10 years of follow-up, patients were categorized into two groups: control (healthy survival, n = 148) and research (adverse events: recurrence or metastasis-related death, n = 84). A training and a test set were established using a 7:3 ratio and a time node. Radiomics features were extracted from axial T2-weighted imaging, contrast-enhanced T1-weighted imaging, and diffusion-weighted imaging (DWI) sequences. The corresponding radiomics scores were generated using the least absolute shrinkage and selection operator algorithm. Kaplan-Meier and multivariate Cox regression analyses were used to screen for independent factors affecting adverse events in patients with TSCC using clinical and pathological results. A novel nomogram was established to predict the probability of adverse events and OS in patients with TSCC. RESULTS: The incidence of adverse events within 2-10 years after surgery was 36.21%. Kaplan-Meier analysis revealed that hot pot consumption, betel nut chewing, platelet-lymphocyte ratio, drug use, neutrophil-lymphocyte ratio, Radscore, and other factors impacted TSCC survival. Multivariate Cox regression analysis revealed that the clinical stage (P < 0.001), hot pot consumption (P < 0.001), Radscore 1 (P = 0.01), and Radscore 2 (P < 0.001) were independent factors affecting TSCC-OS. The same result was validated by the XGBoost algorithm. The nomogram based on the aforementioned factors exhibited good discrimination (C-index 0.86/0.81) and calibration (P > 0.05) in the training and test sets, accurately predicting the risk of adverse events and survival. CONCLUSION: The nomogram constructed using clinical data and MRI radiomics parameters may accurately predict TSCC-OS noninvasively, thereby assisting clinicians in promptly modifying treatment strategies to improve patient prognosis.

Early risk factors of the exacerbation of coronavirus disease 2019 pneumonia.

The purpose of this study was to investigate the early risk factors for the exacerbation of coronavirus disease 2019 (COVID-19) pneumonia. Restrospective analysis of clinical data of 85 patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including gender, age, comorbidities, symptoms, blood routine, clotting profile, biochemical examination, albumin, myocardial enzyme profile, inflammatory markers, and chest computed tomography (CT). All laboratory examinations were measured within first 24 hours after admission, and chest CT was performed before admission. A total of 56 (65.9%) patients had a history of exposure to the Huanan seafood market in Wuhan. Fever and dry cough accounted for the highest percentage of all symptoms. Male COVID-2019 patients were more likely to develop severe pneumonia. Patients with severe and critical conditions are older and have higher rates of hypertension (P = .003) and coronary heart disease (P = .017). All severe and critical patients infected with SARS-CoV-2 showed bilateral lung involvement and have more multiple lobes involvement than common patients (P < .001). Severe and critical patients showed higher white blood cell count (P = .006), neutrophil (NEU) count (P = .001), NEU% (P = .002), procalcitonin (P = .011), C-reactive protein (P = .003), prothrombin time (P = .035), D-dimer (P = .025), aspartate aminotransferase (P = .006), and lower lymphocyte (LYM) count (P = .019), LYM% (P = .001), albumin (P < .001). Logistic regression analysis showed that NEU count is an independent risk factor for deterioration, with the threshold of 6.5 × 109 ·L-1 . We concluded that the laboratory independent risk factor for the progression of COVID-19 pneumonia is NEU count. In addition, COVID-19 patients with bilateral lung involvement or multiple lobes involvement should be taken seriously and actively treated to prevent deterioration of the disease.