Explore the vast range of titles available.

Background: The role of postradiation systemic therapy in non-small cell lung cancer (NSCLC) patients with brain metastasis (BM) was controversial. Thus, we explored the role of Radiation Therapy Oncology Group recursive partitioning analysis (RTOG-RPA) and graded prognostic assessment (GPA) in identifying population who may benefit from postradiation systemic therapy. Methods: The clinical data of NSCLC patients with documented BM from August 2007 to April 2015 of two hospitals were studied retrospectively. Cox regression was used for multivariate analysis. Survival of patients with or without postradiation systemic therapy was compared in subgroups stratified according to RTOG-RPA or GPA. Results: Of 216 included patients, 67.1% received stereotactic radiosurgery (SRS), 24.1% received whole-brain radiation therapy (WBRT), and 8.8% received both. After radiotherapy, systemic therapy was administered in 58.3% of patients. Multivariate analysis found that postradiation systemic therapy (yes vs. no) (hazard ratio [HR] = 0.361, 95% confidence interval [CI] = 0.202-0.648, P = 0.001), radiation technique (SRS vs. WBRT) (HR = 0.462, 95% CI = 0.238-0.849, P = 0.022), extracranial metastasis (yes vs. no) (HR = 3.970, 95% CI = 1.757-8.970, P = 0.001), and Karnofsky performance status (<70 vs. ≥70) (HR = 5.338, 95% CI = 2.829-10.072, P < 0.001) were independent factors for survival. Further analysis found that subsequent tyrosine kinase inhibitor (TKI) therapy could significantly reduce the risk of mortality of patients in RTOG-RPA Class II (HR = 0.411, 95% CI = 0.183-0.923, P = 0.031) or with a GPA score of 1.5-2.5 (HR = 0.420, 95% CI = 0.182-0.968, P = 0.042). However, none of the subgroups stratified according to RTOG-RPA or GPA benefited from the additional conventional chemotherapy. Conclusion: RTOG-RPA and GPA may be useful to identify beneficial populations in NSCLC patients with BM if TKIs were chosen as postradiation systemic therapy.

The purpose of this study was to ascertain a novel prognostic index via recursive partitioning analysis (RPA) in hepatocellular carcinoma (HCC) patients being treated with the combination of atezolizumab plus bevacizumab (ABE) in first-line setting. A total of 784 patients with HCC were included in the analysis. RPA identified three groups of patients: high-risk [Child-Pugh B (CP-B) patients; CP-A and Albumin-Bilirubin (ALBI)-2 patients; CP-A and ALBI-1 patients with macrovascular invasion (MVI), and alpha-fetoprotein (α-FP) ≥400 ng/ml]; intermediate-risk [CP-A and ALBI-1 patients with aspartate aminotransferase (AST) normal value (NV), and αFP ≥400 ng/ml, but without MVI; CP-A and ALBI-1 patients with AST increased value (IV), and neutrophil-lymphocyte ratio (NLR) ≥3, but without MVI]; low-risk (CP-A and ALBI-1 patients with AST NV, and αFP <400 ng/ml, but without MVI; CP-A and ALBI-1 patients with AST IV, and NLR <3, but without MVI; CP-A and ALBI-1 patients with MVI, and αFP <400 ng/ml). Overall survival was 7.0 months in high-risk patients (20.8%), 14.2 months in intermediate-risk patients (19.1%), and 22.5 months in low-risk patients (60.1%). The ABE index allows for easy stratification of HCC patients treated with the combination of ABE in first-line setting.

We assessed prognostic factors in relation to OS from progression in recurrent glioblastomas. Retrospective multicentric study enrolling 407 (training set) and 370 (external validation set) adult patients with a recurrent supratentorial glioblastoma treated by surgical resection and standard combined chemoradiotherapy as first-line treatment. Four complementary multivariate prognostic models were evaluated: Cox proportional hazards regression modeling, single-tree recursive partitioning, random survival forest, conditional random forest. Median overall survival from progression was 7.6 months (mean, 10.1; range, 0–86) and 8.0 months (mean, 8.5; range, 0–56) in the training and validation sets, respectively (p = 0.900). Using the Cox model in the training set, independent predictors of poorer overall survival from progression included increasing age at histopathological diagnosis (aHR, 1.47; 95% CI [1.03–2.08]; p = 0.032), RTOG–RPA V–VI classes (aHR, 1.38; 95% CI [1.11–1.73]; p = 0.004), decreasing KPS at progression (aHR, 3.46; 95% CI [2.10–5.72]; p < 0.001), while independent predictors of longer overall survival from progression included surgical resection (aHR, 0.57; 95% CI [0.44–0.73]; p < 0.001) and chemotherapy (aHR, 0.41; 95% CI [0.31–0.55]; p < 0.001). Single-tree recursive partitioning identified KPS at progression, surgical resection at progression, chemotherapy at progression, and RTOG–RPA class at histopathological diagnosis, as main survival predictors in the training set, yielding four risk categories highly predictive of overall survival from progression both in training (p < 0.0001) and validation (p < 0.0001) sets. Both random forest approaches identified KPS at progression as the most important survival predictor. Age, KPS at progression, RTOG–RPA classes, surgical resection at progression and chemotherapy at progression are prognostic for survival in recurrent glioblastomas and should inform the treatment decisions.

Background Colorectal cancer (CRC) predominantly affects older adults, whose treatment outcomes may be influenced by baseline health-related quality of life (HRQoL). This study aimed to identify predictors of poor preoperative HRQoL in older patients undergoing CRC surgery and to stratify them into risk groups. Methods We retrospectively analyzed data on patients aged ≥65 years who underwent radical CRC surgery at a single medical center in Taiwan (2016-2018). Preoperative HRQoL was assessed using the EORTC QLQ-ELD14 questionnaire and a comprehensive geriatric assessment. Patients were stratified into high or low HRQoL groups based on the median QLQ-ELD14 sum score. Logistic regression identified independent predictors of poor HRQoL, and recursive partitioning analysis (RPA) was applied for risk stratification. Results Among the 179 patients, the most distressing HRQoL domains were Burden of Disease, Maintaining Purpose, and Worries about Others. Independent predictors of poor HRQoL included female sex (adjusted odds ratio [OR] = 2.41, P = 0.029), frailty (adjusted OR = 1.53, P = 0.042), poor Eastern Cooperative Oncology Group (ECOG) performance status (adjusted OR = 2.19, P = 0.008), and lower educational attainment (adjusted OR = 0.23, P = 0.019). RPA identified five patient subgroups with distinct risk levels; frail female had the highest risk (71.4%), while fit patients with college education or higher had the lowest (9.5%). Conclusion Frailty, functional status, sex, and education level are key determinants of preoperative HRQoL in older patients with CRC. The RPA provides a simple tool to identify high-risk patients, allowing targeted preoperative interventions to optimize care and enhance surgical outcomes.

Background: Upfront surgery is a valuable treatment option for oropharyngeal squamous cell carcinoma (OPSCC) and risk stratification is emerging for treatment de-escalation in human papillomavirus (HPV)-related OPSCC. Available prognostic models are either based on selected, mainly non-surgically treated cohorts. Therefore, we investigated unselected OPSCC treated with predominantly upfront surgery. Methods: All patients diagnosed with OPSCC and treated with curative intent between 2000 and 2009 ( n =359) were included. HPV association was determined by HPV-DNA detection and p16 INK4a immunohistochemistry. Predictors with significant impact on overall survival (OS) in univariate analysis were included in recursive partitioning analysis. Results: Risk models generated from non-surgically treated patients showed low discrimination in our cohort. A new model developed for unselected patients predominantly treated with upfront surgery separates low-, intermediate- and high-risk patients with significant differences in 5-year OS (86%, 53% and 19%, P <0.001, respectively). HPV status is the most important parameter followed by T-stage in HPV-related and performance status in HPV-negative OPSCC. HPV status and ECOG remained important parameters in risk models for patients treated with or without surgery. Conclusions: Regardless of treatment strategies, HPV status is the strongest predictor of survival in unselected OPSCC patients. The proposed risk models are suitable to discriminate risk groups in unselected OPSCC patients treated with upfront surgery, which has substantial impact for design and interpretation of de-escalation trials.

Background The Inflammatory burden Index (IBI) is an effective predictor for a range of malignancies. However, the significance of IBI in esophageal squamous cell carcinoma (ESCC) needs to be further verified. The aim of this study was to verify the predictive power of IBI in ESCC undergoing radical resection. Methods The current retrospective study, which comprised 408 ESCC patients randomized into either the primary or validation cohort, evaluated the relationships between IBI, clinical characteristics, and cancer-specific survival (CSS). Additionally, the nomogram model was also constructed and verified. Results The IBI is significantly related to tumor length, vessel invasion, perineural invasion, and TNM stage. Compared to other hematological indices, the decision curve analyses (DCA) and receiver operating characteristic curve (ROC) confirmed the higher prognostic value of IBI, indicating the better clinical applicability. In patients with high IBI compared to the low IBI cohort, the 5-year CSS was considerably worse (total: 27.0% vs. 59.1%, P  < 0.001; primary: 25.0% vs. 58.9%, P  < 0.001; validation: 31.7% vs. 59.7%, P  = 0.002). The IBI was shown to be an independent parameter by multivariate analyses (primary: HR = 2.352, P  < 0.001; validation: HR = 1.683, P  = 0.045). Finally, with the C-index of 0.675 (0.656–0.695) in the primary set and 0.662 (0.630–0.694) in the validation set for CSS in ESCC, an IBI-based nomogram was created and validated. Conclusion The predictive significance of IBI in ESCC patients undergoing radical resection was validated by this investigation. IBI may be utilized for preoperative evaluation of ESCC as it was found to be substantially correlated with prognosis.

Background The high heterogeneity of de novo metastatic nasopharyngeal carcinoma (dmNPC) makes its prognosis and treatment challenging. We aimed to accurately stage dmNPC and assess the patterns of treatment strategies for different risk groups. Methods The study enrolled a total of 562 patients, 264 from 2007 to 2013 in the training cohort and 298 from 2014 to 2017 in the validation cohort. Univariate and multivariate Cox regression analyses were conducted to determine the independent variables for overall survival (OS). Recursive partitioning analysis (RPA) was applied to establish a novel risk-stratifying model based on these variables. Results After pairwise comparisons of OS, three risk groups were generated: low-risk (involved lesions ≤ 4 without liver involvement), intermediate-risk (involved lesions ≤ 4 with liver involvement or involved lesions > 4 with Epstein–Barr virus (EBV)-DNA < 62,000 copies/ml), and high-risk (involved lesions > 4 with EBV-DNA > 62,000 copies/ml). The 3-year OS rate differed significantly between groups (80.4%, 42.0%, and 20.4%, respectively, all P  < 0.05). Adding locoregional intensity-modulated radiotherapy (LRRT) followed by palliative chemotherapy (PCT) resulted in a significant OS benefit over PCT alone for the low- and intermediate-risk groups ( P  = 0.0032 and P  = 0.0014, respectively). However, it provided no survival benefits for the high-risk group ( P  = 0.6). Patients did not benefit from concurrent chemotherapy during LRRT among the three subgroups ( P  = 0.12, P  = 0.13, and P  = 0.3, respectively). These results were confirmed with the validation cohort. Conclusions The novel RPA model revealed superior survival performance in subgroup stratification and could facilitate more effective treatment strategies for dmNPC.

Background Glioma is the most common primary brain tumor with high mortality and disability rates. Recent studies have highlighted the significant prognostic consequences of subtyping molecular pathological markers using tumor samples, such as IDH, 1p/19q, and TERT. However, the relative importance of individual markers or marker combinations in affecting patient survival remains unclear. Moreover, the high cost and reliance on postoperative tumor samples hinder the widespread use of these molecular markers in clinical practice, particularly during the preoperative period. We aim to identify the most prominent molecular biomarker combination that affects patient survival and develop a preoperative MRI-based predictive model and clinical scoring system for this combination. Methods A cohort dataset of 2,879 patients was compiled for survival risk stratification. In a subset of 238 patients, recursive partitioning analysis (RPA) was applied to create a survival subgroup framework based on molecular markers. We then collected MRI data and applied Visually Accessible Rembrandt Images (VASARI) features to construct predictive models and clinical scoring systems. Results The RPA delineated four survival groups primarily defined by the status of IDH and TERT mutations. Predictive models incorporating VASARI features and clinical data achieved AUC values of 0.85 for IDH and 0.82 for TERT mutations. Nomogram-based scoring systems were also formulated to facilitate clinical application. Conclusions The combination of IDH-TERT mutation status alone can identify the most distinct survival differences in glioma patients. The predictive model based on preoperative MRI features, supported by clinical assessments, offers a reliable method for early molecular mutation prediction and constitutes a valuable scoring tool for clinicians in guiding treatment strategies.

This study aimed to evaluate age as a prognostic factor and develop a comprehensive prognostic model for patients undergoing clipping surgery for World Federation of Neurosurgical Societies (WFNS) grade I/II aneurysmal subarachnoid haemorrhage (SAH). We retrospectively investigated 188 patients with WFNS grade I/II SAH who underwent microsurgical clipping at our institute between December 2010 and January 2020. The data of 176 patients (75 with grade I and 101 with grade II) were analysed. Data on patient demographics, aneurysm characteristics, SAH factors, surgical details, and clinical outcomes were collected. Prognostic factors were assessed using bivariate and multivariable logistic regression analyses, and recursive partitioning analysis. Favourable outcomes (mRS 0–2) were observed in 76% of patients. Age, a significant negative prognostic factor in multivariable analysis (odds ratio 0.55, 95% confidence interval 0.40–0.76, p  < 0.001), was cutoff at 70 years by the receiver operating characteristic curve. Patients aged ≤ 70 years had significantly better outcomes than those aged > 70 years (84% vs. 46%, respectively; p  < 0.001). Epileptic seizures were significantly associated with poor outcomes in older adults ( p  < 0.001). A prognostic model (favourable, intermediate, and poor) based on age and postoperative adverse events showed significantly different outcomes between age groups ( p  < 0.001). Age was a stronger prognostic factor than WFNS grading for patients with grade I/II SAH undergoing microsurgical clipping. For patients aged ≤ 70 years, precise microsurgeries with fewer complications were associated with favourable outcomes beyond WFNS grade. For older patients, postoperative intensive seizure management may prevent poor outcomes.