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OBJECTIVE To evaluate the prognostic performance of the revised 2018 FIGO staging system for cervical cancer. METHODS This retrospective multicenter study enrolled cervical cancer patients with 2009 FIGO Stage IA1-IIA2 who underwent surgeries between January 2006 and December 2017 in four tertiary hospitals. Patients were restaged according to the 2018 FIGO staging system by reviewing their medical data. RESULTS Of 3238 cervical cancer patients included, 1841 (56.9%) patients were restaged: 641 (34.9%) due to tumor size, 544 (29.5%) due to lymph node metastasis, 614 (33.4%) due to the inconsistency between pre- and postoperative assessments, and 42 due to the cancellation of invasion width in Stage IA. After restaging, a clear tendency of decreased recurrence-free survival (RFS) and overall survival (OS) with increasing stage was observed. Multivariate Cox analysis showed that 2018 FIGO stage, parametrial involvement, and histology were independent prognostic factors for both OS and RFS (P

Jijin Yao,1,2,* Ying Wang,3,* Yujing Lin,4 Yingying Yang,5 Jingjing Wan,3 Xiaohua Gong,1 Fanwei Zhang,3 Wangjian Zhang,6 Tia Marks,7 Siyang Wang,1 Hongjun Jin,2 Hong Shan2,8 1The Cancer Center of the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of China; 2Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of China; 3Department of Nuclear Medicine, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of China; 4Department of Pathology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, 519001, People’s Republic of China; 5Department of Pharmacy, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of China; 6Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, People’s Republic of China; 7Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, NY, 12144, USA; 8Department of Interventional Medicine, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hongjun JinGuangdong Provincial Key Laboratory of Biomedical Imaging, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of ChinaEmail jinhj3@mail.sysu.edu.cnHong ShanDepartment of Interventional Medicine, Guangdong Provincial Key Laboratory of Biomedical Imaging, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, People’s Republic of ChinaEmail shanhong@mail.sysu.edu.cnIntroduction: To evaluate the role of maximal standardized uptake values (SUVmax) and total lesion glycolysis (TLG) from serial 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for early prediction of neoadjuvant chemotherapy (NAC) response in locoregionally advanced nasopharyngeal carcinoma (LANPC).Methods: A total of 121 LANPC patients who completed pretreatment 18F-FDG PET/CT between June 2017 and July 2020 were retrospectively included. The median age of all the participants was 50 years old (range: 19– 74 years), with 94 (77.7%) males and 27 (22.3%) females. The SUVmax from the primary tumor site (SUVmax-PT) and the total lesion glycolysis from the primary tumor site (TLG-PT) were recorded. Tumor response was calculated according to the Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 Criteria at two-week post-secondary NAC cycle. Patients who achieved an objectively partial or full reaction after two cycles of NAC were defined as ‘responders’, and patients who obtained stability or progression were classified as ‘non-responders’.Results: After two cycles of NAC, 96 patients were categorized as “responders” and 25 patients as “non-responders”. The optimal thresholds of the SUVmax-PT were 11.8 and 38.5 for the TLG-PT. Non-responders were significantly associated with high SUVmax-PT (HR, 3.49; 95% CI, 1.17– 10.36; p = 0.024) and TLG-PT (HR, 4.45; 95% CI, 1.44– 13.78; p = 0.010) in multivariate analysis. Recursive partitioning analysis (RPA) categorized patients into three prognostic groups based on SUVmax-PT and TLG-PT: high-response group, intermediate-response group, and low-response group, with corresponding favorable response rates of 94%, 80%, and 55%, respectively. Moreover, a nomogram was created based on metabolic parameters that precisely projected an individual’s response of NAC (C-index, 0.787; 95% CI, 0.533– 1.000).Conclusion: Pretreatment 18F-FDG PET/CT to measure SUVmax-PT and TLG-PT could be a useful non-invasive method for early indication of NAC efficacy. The nomogram based on PET/CT parameters may potentially provide direction for treatment decisions based on NAC levels.Keywords: nasopharyngeal carcinoma, neoadjuvant chemotherapy, tumor response, PET/CT, nomogram

Background In the absence of practical and reliable predictors for whether the endocervical curettage (ECC) procedure should be performed, decisions regarding patient selection are usually based on the colposcopists’ clinical judgment instead of evidence. We aimed to develop and validate a practical prediction model that uses available information to reliably estimate the need to perform ECC in patients suspected of having cervical lesions. Methods In this retrospective study, 2088 patients who underwent colposcopy, colposcopically directed biopsy (CDB) and ECC procedures between September 2019 and September 2020 at the Second Hospital of Shanxi Medical University were included. The data were analyzed with univariate and multivariable logistic regression. Least absolute shrinkage and selection operator (LASSO) was used to select predictors for ECC positivity. The ECC prediction model was presented as a nomogram and evaluated in terms of discrimination and calibration. Furthermore, this model was validated internally with cross-validation and bootstrapping. Results Significant trends were found for ECC positivity with increasing age (P = 0.001), menopause (P = 0.003), Human papillomavirus (HPV) status (P P P = 0.037) and colposcopy impression (P Conclusions A readily applicable clinical prediction model was constructed to reliably estimate the probability of ECC positivity in patients suspicious of having cervical lesions, which may help clinicians make decisions regarding the ECC procedure and possibly prevent adverse effects.

In order to develop a novel scoring model for the prediction of coronavirus disease-19 (COVID-19) patients at high risk of severe disease, we retrospectively studied 419 patients from five hospitals in Shanghai, Hubei, and Jiangsu Provinces from January 22 to March 30, 2020. Multivariate Cox regression and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were both used to identify high-risk factors for disease severity in COVID-19 patients. The prediction model was developed based on four high-risk factors. Multivariate analysis showed that comorbidity [hazard ratio (HR) 3.17, 95% confidence interval (CI) 1.96–5.11], albumin (ALB) level (HR 3.67, 95% CI 1.91–7.02), C-reactive protein (CRP) level (HR 3.16, 95% CI 1.68–5.96), and age ≥60 years (HR 2.31, 95% CI 1.43–3.73) were independent risk factors for disease severity in COVID-19 patients. OPLS-DA identified that the top five influencing parameters for COVID-19 severity were CRP, ALB, age ≥60 years, comorbidity, and lactate dehydrogenase (LDH) level. When incorporating the above four factors, the nomogram had a good concordance index of 0.86 (95% CI 0.83–0.89) and had an optimal agreement between the predictive nomogram and the actual observation with a slope of 0.95 (R2 = 0.89) in the 7-day prediction and 0.96 (R2 = 0.92) in the 14-day prediction after 1,000 bootstrap sampling. The area under the receiver operating characteristic curve of the COVID-19-American Association for Clinical Chemistry (AACC) model was 0.85 (95% CI 0.81–0.90). According to the probability of severity, the model divided the patients into three groups: low risk, intermediate risk, and high risk. The COVID-19-AACC model is an effective method for clinicians to screen patients at high risk of severe disease.

Background Cumulating evidence indicates that the systemic inflammatory response (SIR) plays a crucial role in the prognosis of various cancers. We aimed to generate a preoperative risk grade (PRG) by integrating SIR markers to preoperatively predict the long-term prognosis of intrahepatic cholangiocarcinoma (ICC). Methods 468 consecutive ICC patients who underwent hepatectomy between 2010 and 2017 were enrolled. The PRG and a nomogram were generated and their predictive accuracy was evaluated. Results The PRG consisted of two non-tumor-specific SIR markers platelet-to-lymphocyte ratio (PLR) and albumin (ALB), which were both the independent predictors of overall survival (OS). Multivariate analysis showed that the PRG was significantly associated with OS (PRG = 1: hazard ratio (HR) = 3.800, p p p p Conclusions The PRG integrating two non-tumor-specific SIR markers PLR and ALB was a novel method to preoperative predicting the prognosis of ICC.

Objectives To develop and validate a pre-transcatheter arterial chemoembolization (TACE) MRI-based radiomics model for predicting tumor response in intermediate-advanced hepatocellular carcinoma (HCC) patients. Materials Ninety-nine intermediate-advanced HCC patients (69 for training, 30 for validation) treated with TACE were enrolled. MRI examinations were performed before TACE, and the efficacy was evaluated according to the mRECIST criterion 3 months after TACE. A total of 396 radiomics features were extracted from T2-weighted pre-TACE images, and least absolute shrinkage and selection operator (LASSO) regression was applied to feature selection and model construction. The performance of the model was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results The AFP value, Child-Pugh score, and BCLC stage showed a significant difference between the TACE response (TR) and non-TACE response (nTR) patients. Six radiomics features were selected by LASSO and the radiomics score (Rad-score) was calculated as the sum of each feature multiplied by the non-zero coefficient from LASSO. The AUCs of the ROC curve based on Rad-score were 0.812 and 0.866 in the training and validation cohorts, respectively. To improve the diagnostic efficiency, the Rad-score was further integrated with the above clinical indicators to form a novel predictive nomogram. Results suggested that the AUC increased to 0.861 and 0.884 in the training and validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful. Conclusion The radiomics and clinical indicator-based predictive nomogram can well predict TR in intermediate-advanced HCC and can further be applied for auxiliary diagnosis of clinical prognosis. Key Points • The therapeutic outcome of TACE varies greatly even for patients with the same clinicopathologic features. • Radiomics showed excellent performance in predicting the TACE response. • Decision curves demonstrated that the novel predictive model based on the radiomics signature and clinical indicators has great clinical utility.

Objective The aim of the study was to establish an effective prognostic nomogram for esophageal squamous cell carcinoma after radical esophagectomy followed by adjuvant chemotherapy in those previously untreated patients. Methods The clinicopathological data from 328 patients who underwent radical esophagectomy followed by adjuvant chemotherapy or not at the Tianjin Medical University Cancer Institute and Hospital between 2006 and 2010 were retrospectively studied. Nomograms which predicted survival of esophageal squamous cell carcinoma were established based on the Cox proportional hazards regression model. To determine its predictive accuracy and discriminatory capacity, the concordance index and calibration curve were calculated after bootstrapping in the internal validation. An external validation of 76 patients in 2011 was prospectively studied at the same institution. To verify the performance of the nomogram, the comparison between the nomogram and Tumor-Node-Metastasis staging system was conducted. Results The 5-year overall survival was 43.1% in the primary cohort. Based on multivariate analyses, five independent prognostic variables including gender, tumor length, T stage, N stage and chemotherapy cycles were selected to build the nomograms to predict disease-free survival and overall survival. The concordance index of the nomogram to predict overall survival was 0.71 (95% confidence interval, 0.63-0.79), which was superior to the predictive power of Tumor-Node-Metastasis staging system (0.64) in the primary cohort. Meanwhile, the calibration curve showed good accuracy between predictive and actual overall survival. In the validation cohort, the concordance index (0.77) and calibration plot displayed favorable performances. The other nomogram to predict disease-free survival also performed well. Conclusions The prognostic nomogram provided individualized risk estimate of survival in patients after esophagectomy followed by adjuvant chemotherapy.

Purpose This study was conducted to assess the relationship and prognostic significance between preoperative serum albumin to globulin ratio (AGR) and high-resolution computed tomography (HRCT) features of non-small cell lung cancer (NSCLC). Materials and methods Demographic parameters, laboratory values including AGR and other clinical variables were evaluated in 180 patients with NSCLC, and 72 of these patients had results of radiology parameters detected with HRCT [including emphysema, tumor disappearance rate (TDR), CT values and CT enhanced values of the tumor mass] were assessed for survival analyses. The 72 patients were divided into two groups: normal lung group and emphysema group. The discriminatory values for AGR between these two groups were assessed by Mann–Whitney U test The relationship between TDR and AGR in NSCLC patients was evaluated by Pearson correlation analysis. Results In multivariate analysis, TDR (p = 0.033), AGR (p = 0.038), emphysema (p = 0.009), and N stage (P = 0.026) were independent predictors of overall survival (OS). AGR was higher in NSCLC patients without emphysema than NSCLC patients with emphysema (z = −2.979, P = 0.003). TDR demonstrated that there was a positive relationship with AGR (r = 0.307, p = 0.009). A nomogram with AGR, TDR, emphysema, and N stage was established to predict 5-year survival. Conclusions There is a relationship between CT features and AGR in NSCLC. The integrative nomogram combined with CT images, clinical and hematologic features improved survival prediction in NSCLC patients, which offers a non-invasive, comprehensive, and convenient evaluation for individualized management of NSCLC patients.