Preoperative prediction of microsatellite instability status: development and validation of a pan-cancer PET/CT-based radiomics model.

OBJECTIVE: The purpose of this study is to verify the feasibility of preoperative prediction of patients' microsatellite instability status by applying a PET/CT-based radiation model. METHODS: This retrospective study ultimately included 142 patients. Three prediction models have been developed. The predictive performance of all models was evaluated by the receiver operating characteristic curve and area under the curve values. The PET/CT radiological histology score (Radscore) was calculated to evaluate the microsatellite instability status, and the corresponding nomogram was established. The correlation between clinical factors and radiological characteristics was analyzed to verify the value of radiological characteristics in predicting microsatellite instability status. RESULTS: Twelve features were retained to establish a comprehensive prediction model of radiological and clinical features. M phase of the tumor has been proven to be an independent predictor of microsatellite instability status. The receiver operating characteristic results showed that the area under the curve values of the training set and the validation set of the radiomics model were 0.82 and 0.75, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the training set were 0.72, 0.78, 0.83 and 0.66, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the validation set were 1.00, 0.50, 0.76 and 1.00, respectively. The risk of patients with microsatellite instability was calculated by Radscore and nomograph, and the cutoff value was -0.4385. The validity of the results was confirmed by the decision and calibration curves. CONCLUSION: Radiological models based on PET/CT can provide clinical and practical noninvasive prediction of microsatellite instability status of several different cancer types, reducing or avoiding unnecessary biopsy to a certain extent.

PET/CT-based radiomics analysis may help to predict neoadjuvant chemotherapy outcomes in breast cancer.

Background: The aim of this study was to evaluate the clinical usefulness of radiomics signature-derived 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) for the early prediction of neoadjuvant chemotherapy (NAC) outcomes in patients with (BC). Methods: A total of 124 patients with BC who underwent pretreatment PET-CT scanning and received NAC between December 2016 and August 2019 were studied. The dataset was randomly assigned in a 7:3 ratio to either the training or validation cohort. Primary tumor segmentation was performed, and radiomics signatures were extracted from each PET-derived volume of interest (VOI) and CT-derived VOI. Radiomics signatures associated with pathological treatment response were selected from within a training cohort (n = 85), which were then applied to generate different classifiers to predict the probability of pathological complete response (pCR). Different models were then independently tested in the validation cohort (n = 39) regarding their accuracy, sensitivity, specificity, and area under the curve (AUC). Results: Thirty-five patients (28.2%) had pCR to NAC. Twelve features consisting of five PET-derived signatures, four CT-derived signatures, and three clinicopathological variables were candidates for the model's development. The random forest (RF), k-nearest neighbors (KNN), and decision tree (DT) classifiers were established, which could be utilized to predict pCR to NAC with AUC ranging from 0.819 to 0.849 in the validation cohort. Conclusions: The PET/CT-based radiomics analysis might provide efficient predictors of pCR in patients with BC, which could potentially be applied in clinical practice for individualized treatment strategy formulation.

PET/CT Radiomic Features: A Potential Biomarker for EGFR Mutation Status and Survival Outcome Prediction in NSCLC Patients Treated With TKIs.

Backgrounds: Epidermal growth factor receptor (EGFR) mutation profiles play a vital role in treatment strategy decisions for non-small cell lung cancer (NSCLC). The purpose of this study was to evaluate the predictive efficacy of baseline 18F-FDG PET/CT-based radiomics analysis for EGFR mutation status, mutation site, and the survival benefit of targeted therapy. Methods: A sum of 313 NSCLC patients with pre-treatment 18F-FDG PET/CT scans and genetic mutations detection were retrospectively studied. Clinical and PET metabolic parameters were incorporated into independent predictors of determining mutation status and mutation site. The dataset was randomly allocated into the training and the validation sets in a 7:3 ratio. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with EGFR mutation profiles is built by feature selection. Three different prediction models based on support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers were established. Furthermore, nomograms for estimation of overall survival (OS) and progression-free survival (PFS) were established by integrating PET/CT radiomics score (Rad-score), metabolic parameters, and clinical factors. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis and the calibration curve analysis. The decision curve analysis (DCA) was applied to estimate and compare the clinical usefulness of nomograms. Results: Three hundred thirteen NSCLC patients were classified into a training set (n=218) and a validation set (n=95). Multivariate analysis demonstrated that SUVmax and sex were independent indicators of EGFR mutation status and mutation site. Eight CT-derived RS, six PET-derived RS, and two clinical factors were retained to develop integrated models, which exhibited excellent ability to distinguish between EGFR wild type (EGFR-WT), EGFR 19 mutation type (EGFR-19-MT), and EGFR 21 mutation type (EGFR-21-MT). The SVM model outperformed the RF model and the DT model, yielding training area under the curves (AUC) of EGFR-WT, EGFR-19-WT, and EGFR-21-WT, with 0.881, 0.851, and 0.849, respectively, and validation AUCs of 0.926, 0.805 and 0.859, respectively. For prediction of OS, the integrated nomogram is superior to the clinical nomogram and the radiomics nomogram, with C-indexes of 0.80 in the training set and 0.83 in the validation set, respectively. Conclusions: The PET/CT-based radiomics analysis might provide a novel approach to predict EGFR mutation status and mutation site in NSCLC patients and could serve as useful predictors for the patients' survival outcome of targeted therapy in clinical practice.

Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using 18F-FDG PET/CT Images.

Background: Lymph vascular invasion (LVI) is an unfavorable prognostic indicator in gastric cancer (GC). However, there are no reliable clinical techniques for preoperative predictions of LVI. The aim of this study was to develop and validate PET/CT-based radiomics signatures for predicting LVI of GC preoperatively. Radiomics nomograms were also established to predict patient survival outcomes. Methods: This retrospective study registered 148 GC patients with histopathological confirmation for LVI status, who underwent pre-operative PET/CT scans (Discovery VCT 64 PET/CT system) from December 2014 to June 2019. Clinic-pathological factors (age, gender, and tumor grade, etc.) and metabolic PET data (maximum and mean standardized uptake value, total lesion glycolysis and metabolic tumor volume) were analyzed to identify independent LVI predictors. The dataset was randomly assigned to either the training set or test set in a 7:3 ratios. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with LVI status is built by feature selection. Four models with different modalities (PET-RS: only PET radiomics features; CT-RS: only CT radiomics features; PET/CT-RS: both PET and CT radiomics features; PET/CT-RS plus clinical data) were developed to predict LVI. Patients were postoperatively followed up with PET/CT every 6-12 months for the first two years and then annually up to five years after surgery. The PET/CT radiomics score (Rad-scores) was calculated to assess survival outcome, and corresponding nomograms with radiomics (NWR) or without radiomics (NWOR) were established. Results: Tumor grade and maximum standardized uptake value (SUVmax) were the independent LVI predictor. 1037 CT and PET 3D radiomics features were extracted separately and reduced to 4 and 5 features to build CT-RS and PET-RS, respectively. PET/CT-RS and PET/CT-RS plus clinical data (tumor grade and SUVmax) were also developed. The ROC analysis demonstrated clinical usefulness of PET/CT-RS plus clinical data (AUC values for training and validation, respectively 0.936 and 0.914) and PET/CT-RS (AUC values for training and validation, respectively 0.881 and 0.854), which both are superior to CT-RS (0.838 and 0.824) and PET-RS (0.821 and 0.812). SUVmax and LVI were independent prognostic indicators of both OS and PFS. Decision curve analysis (DCA) demonstrated NWR outperformed NWOR and was established to assess survival outcomes. For estimation of OS and PFS, the C-indexes of the NWR were 0. 88 and 0.88 in the training set, respectively, while the C-indexes of the NWOR were 0. 82 and 0.85 in the training set, respectively. Conclusions: The PET/CT-based radiomics analysis might serve as a non-invasive approach to predict LVI status in GC patients and provide effective predictors of patient survival outcomes.

A deep learning radiomics model may help to improve the prediction performance of preoperative grading in meningioma.

PURPOSE: This study aimed to investigate the clinical usefulness of the enhanced-T1WI-based deep learning radiomics model (DLRM) in differentiating low- and high-grade meningiomas. METHODS: A total of 132 patients with pathologically confirmed meningiomas were consecutively enrolled (105 in the training cohort and 27 in the test cohort). Radiomics features and deep learning features were extracted from T1 weighted images (T1WI) (both axial and sagittal) and the maximum slice of the axial tumor lesion, respectively. Then, the synthetic minority oversampling technique (SMOTE) was utilized to balance the sample numbers. The optimal discriminative features were selected for model building. LightGBM algorithm was used to develop DLRM by a combination of radiomics features and deep learning features. For comparison, a radiomics model (RM) and a deep learning model (DLM) were constructed using a similar method as well. Differentiating efficacy was determined by using the receiver operating characteristic (ROC) analysis. RESULTS: A total of 15 features were selected to construct the DLRM with SMOTE, which showed good discrimination performance in both the training and test cohorts. The DLRM outperformed RM and DLM for differentiating low- and high-grade meningiomas (training AUC: 0.988 vs. 0.980 vs. 0.892; test AUC: 0.935 vs. 0.918 vs. 0.718). The accuracy, sensitivity, and specificity of the DLRM with SMOTE were 0.926, 0.900, and 0.924 in the test cohort, respectively. CONCLUSION: The DLRM with SMOTE based on enhanced T1WI images has favorable performance for noninvasively individualized prediction of meningioma grades, which exhibited favorable clinical usefulness superior over the radiomics features.

Quality-adjusted survival in patients with metastatic colorectal cancer treated with fruquintinib in the FRESCO trial.

Aim: To assess whether the survival benefit of fruquintinib is quality-adjusted. Materials & methods: Data of 416 metastatic colorectal cancer patients from the Phase III FRESCO trial were used. The Quality-adjusted Time Without Symptoms or Toxicity (Q-TWiST) analysis assessed the quality-adjusted survival benefit of fruquintinib versus placebo, accounting for freedom from symptomatic disease and from severe side effects of treatment. Results: Fruquintinib significantly improved patients' Q-TWiST (difference: 2.23 [1.41, 3.04] months) versus placebo. The Q-TWiST gain was 28.3% in the base case and ranged from 16.7 to 39.9% in the threshold analysis, favoring fruquintinib. The Q-TWiST benefit was observed in fruquintinib-treated patients regardless of prior targeted therapy. Conclusion: Fruquintinib provides a clinically meaningful quality-adjusted survival benefit versus placebo as a third-line treatment for metastatic colorectal cancer patients.

Lay abstract The objective of the study was to assess the benefit of fruqintinib, a chemotherapy drug for patients with metastatic colorectal cancer (mCRC) who do not respond well to previous chemotherapy. The study considered both the time of survival and the quality of life after patients received fruqintinib. In measuring patients' quality of life, the study assessed the time that was free from cancer symptoms and any severe side effects from treatment. The study used data obtained from a Phase III clinical trial, FRESCO, which included 416 mCRC patients receiving fruqintinib or placebo. The results showed that fruqintinib significantly extended patients' symptom-free and side effects-free survival time by approximately 2 months and 5 days. Fruqintinib was 16.7­39.9% more effective than placebo in extending mCRC patients' high-quality life, regardless of prior targeted therapy.

Surufatinib in advanced extrapancreatic neuroendocrine tumours (SANET-ep): a randomised, double-blind, placebo-controlled, phase 3 study.

BACKGROUND: Therapeutic options for advanced neuroendocrine tumours (NETs) are limited. We investigated the efficacy and safety of surufatinib (HMPL-012, sulfatinib) in patients with extrapancreatic NETs. METHODS: SANET-ep was a randomised, double-blind, placebo-controlled, phase 3 trial undertaken at 24 hospitals across China. Patients (aged 18 years or older) with unresectable or metastatic, well differentiated, extrapancreatic NETs, with an Eastern Cooperative Oncology Group performance status of 0 or 1, and progression on no more than two types of previous systemic regimens were enrolled. Patients were centrally randomly assigned (2:1) using stratified block randomisation (block size 3) via an interactive web response system to receive oral surufatinib at 300 mg per day or matching placebo. Randomisation was stratified by tumour origin, pathological grade, and previous treatment. Patients, investigators, research staff and the sponsor study team were masked to treatment allocation. Crossover to the surufatinib group was allowed for patients in the placebo group at disease progression. The primary endpoint was investigator-assessed progression-free survival, which was analysed in the intention-to-treat population. A preplanned interim analysis was done at 70% of predicted progression-free survival events. This study was registered with ClinicalTrials.gov, NCT02588170. Follow-up is ongoing. FINDINGS: Between Dec 9, 2015, and March 31, 2019, 198 patients were randomly assigned to surufatinib (n=129) or placebo (n=69). Median follow-up was 13·8 months (95% CI 11·1-16·7) in the surufatinib group and 16·6 months (9·2-not calculable) in the placebo group. Investigator-assessed median progression-free survival was 9·2 months (95% CI 7·4-11·1) in the surufatinib group versus 3·8 months (3·7-5·7) in the placebo group (hazard ratio 0·33; 95% CI 0·22-0·50; p<0·0001). As the trial met the predefined criteria for early discontinuation of the study at the interim analysis, the study was terminated early, as recommended by the independent data monitoring committee. The most common treatment-related adverse events of grade 3 or worse were hypertension (47 [36%] of 129 patients in the surufatinib group vs nine [13%] of 68 patients in the placebo group) and proteinuria (25 [19%] vs zero). Treatment-related serious adverse events were reported in 32 (25%) of 129 patients in the surufatinib group and nine (13%) of 68 patients in the placebo group. Treatment-related deaths occurred in three patients in the surufatinib group (disseminated intravascular coagulation and hepatic encephalopathy, liver injury, and death with unknown reason) and one patient in the placebo group (cachexia and respiratory failure). INTERPRETATION: Progression-free survival was significantly longer in patients given surufatinib compared with patients given placebo, and surufatinib has a favourable benefit-to-risk profile in patients with progressive, advanced, well differentiated extrapancreatic NETs. Our results suggest that surufatinib might be a new treatment option for this population. FUNDING: Hutchison MediPharma.

A Phase III, randomized, double-blind, placebo-controlled, multicenter study of fruquintinib in Chinese patients with advanced nonsquamous non-small-cell lung cancer - The FALUCA study.

OBJECTIVES: Fruquintinib is an orally active kinase inhibitor that selectively targets the vascular endothelial growth factor (VEGF) receptor. A Phase II trial has demonstrated a significant benefit in progression-free survival (PFS) for fruquintinib-treated patients with locally advanced/metastatic nonsquamous non-small-cell lung cancer (NSCLC) who have progressed after second-line chemotherapy. This Phase III trial is a randomized, double-blind, multicenter trial to confirm fruquintinib's efficacy in the same patient population. MATERIALS AND METHODS: From December 2015 to February 2018, 730 patients were screened, of whom 527 were enrolled into the study. Participants were randomized 2:1 to receive fruquintinib (n = 354) or placebo (n = 173) once daily for 3 weeks on-treatment, and 1 week off-treatment. Patients were stratified according to epidermal growth factor receptor mutation status and prior use of VEGF inhibitors. Primary endpoint was overall survival (OS). RESULTS: Median OS was 8.9 months for the fruquintinib group and 10.4 months for placebo group (hazard ratio [HR] 1.02; 95 % confidence interval [CI], 0.82-1.28; P = 0.841), with median PFS of 3.7 months and 1.0 months, respectively (HR 0.34; 95 % CI, 0.28-0.43; P < 0.001). Objective response rate and disease control rate were 13.8 % and 66.7 % for fruquintinib, and 0.6 % and 24.9 % for placebo, respectively (P < 0.001). Hypertension was the most frequent treatment-emergent adverse event (≥grade 3) observed in fruquintinib-treated patients (21.0 %). Post hoc analysis revealed that fruquintinib prolonged the median OS for patients who did not receive subsequent antitumor therapy: 7.0 months versus 5.1 months for placebo (HR 0.65; 95 % CI, 0.46-0.91; P = 0.012). Patients receiving fruquintinib also reported improvements in quality of life for most functional scales measured by EORTC QLQ-C30 and LC13 questionnaires. CONCLUSION: Although the study did not meet its primary endpoint, fruquintinib could be effective in combination with other agents for the treatment of patients with NSCLC who have failed second-line chemotherapy.

Response and remission rates in Chinese patients with bipolar mania treated for 4 weeks with either quetiapine or lithium: a randomized and double-blind study.

OBJECTIVE: To assess the efficacy and tolerability of quetiapine in Chinese patients hospitalized with acute bipolar mania. METHODS: This was a 4-week, multicenter, randomized, double-blind, lithium-controlled, parallel-group study. Secondary endpoints in the primary analysis were: response rate (> or = 50% decrease from baseline in YMRS total score) and remission rate as defined using 3 criteria: YMRS total score < or = 12, YMRS total score < or = 12 + MADRS total score < or = 8, and YMRS total score < or = 8. Other measures included: change from baseline at Day 28 in YMRS, PANSS, and MADRS total score. Adverse event (AE) data were collected throughout the study. RESULTS: 73 (94.8%) quetiapine and 62 (80.5%) lithium patients completed the study. Mean (SD) quetiapine doses for the ITT population and responders were 648.2 (111.84)mg/day and 637.5 (118.78)mg/day, respectively, while mean lithium concentrations for the ITT population and responders were 0.80 (0.28)mmol/L and 0.80 (0.22)mmol/L, respectively. Of patients who responded to quetiapine at Day 28, 88.3% were receiving 600-800mg/day. At Day 28 YMRS response rate was significantly greater with quetiapine than lithium (77.9% vs. 59.7%, p = 0.0132), and remission rates using the 3 criteria were significantly greater with quetiapine than lithium: YMRS total score < or = 12 (70.1% vs. 48.1%, p = 0.0071), YMRS < or = 12 + MADRS < or = 8 (70.1% vs. 48.1%; p = 0.0071), and YMRS < or = 8 (51.9% vs. 32.5%; p = 0.0147). Significant decreases were observed in PANSS, YMRS, and MADRS total scores for both groups. The most common AEs experienced by patients receiving quetiapine were constipation, dizziness, diarrhea, alanine aminotransferase increase, palpitations, aspartate aminotransferase increase, pharyngolaryngeal pain, upper respiratory tract infection and dry mouth. In patients receiving lithium, the most common AEs were nausea (16.9%), constipation (13.0%), vomiting (13.0%), nasopharyngitis (11.7%), dizziness (6.5%), diarrhea (6.5%), and upper respiratory tract infection (6.5%). CONCLUSION: Quetiapine was shown to be clinically effective in patients with acute bipolar mania. There were side effects with quetiapine similar to those reported in other studies that included other ethnic populations of patients.