Recursive Partitioning Research Articles

OS13.6.A SURVIVAL IS ASSOCIATED WITH CIRCULATING B-CELLS AND AGE AMONG OLIGODENDROGLIOMA PATIENTS

Abstract BACKGROUND Though patients with oligodendroglioma have improved outcomes versus astrocytomas, there remains marked variability in their survival experience that is unexplained by known prognostic factors. Immunomethylomics uses DNA methylation as a substitute for flow cytometry to characterize immune cells in whole blood. We applied immunomethylomics to archived samples from patients with oligodendroglioma enrolled in the UCSF Adult Glioma Study (AGS) to assess the impact of immune-related characteristics on prognosis. MATERIAL AND METHODS We used immunomethylomics to evaluate immune cell fractions in archived whole blood from the AGS. We identified 141 patients with oligodendroglioma (IDH and TERT mutant, and 1p19q co-deleted) and compared them to other adult diffuse glioma subtypes (N = 347) and controls (N = 454). RESULTS The median age at diagnosis of the 141 oligodendrogliomas was 44 years (range 19 - 83), 57% were male, and 75% white. A total of 60% of patients had received chemotherapy, with or without radiation, prior to blood draw and 25% were taking dexamethasone at the time of sample collection. Oligodendroglioma patients had lower proportions of B cell fractions (total, memory, naïve) than people without glioma. Still, there were higher proportions of B cell (total, memory) and lymphocyte fractions (total, CD4-total and memory), basophil, eosinophil, and NK cells in oligodendrogliomas compared to other glioma subtypes. Median overall survival for the oligodendrogliomas was 17.5 years (95% CI 16.9 - NA) with median follow-up time of 12 years (95% CI 11 - 14). Recursive partitioning analysis delineated two statistically significantly different survival groups for oligodendroglioma patients based on an interaction between age at diagnosis and B naïve cell proportions. The group with the best outcome had a median survival of 24.2 years (95% CI 20.4 - NR) comprised of patients </= 42 years of age with a higher proportion of B naïve cells (>1.91%) (N = 37). The group with the worse outcome had a median survival of 16.9 years (14.8 - NR) and included patients </= 42 years of age with a lower proportion of B naïve cells (</= 1.91%) (N = 28) OR patients > 42 years of age (N = 76) (p = 0.00032). Additionally, proportions of lymphocyte fractions (CD4 and CD8 total, memory, and naïve) were significantly lower in the worse outcome group. Grade or prior treatment did not differ between the groups. CONCLUSION We identified an interaction between age and B naïve cell proportions that distinguished survival outcomes for patients with oligodendrogliomas. Immunomethylomics is a powerful tool for assessing immune status and these findings suggest that blood-immune characteristics may play a vital role in the prognosis of patients with gliomas.

Relationship between transcriptional expression of pyruvate dehydrogenase and local control of disease in patients with oral cavity carcinomas

BackgroundThe altered cellular metabolism is one of the hallmarks of the cancer cells, favoring the process of aerobic glycolysis, known as the Warburg effect. The pyruvate dehydrogenase (PDH) complex is one of the elements involved in this metabolic process. The present study aims to evaluate the relationship between the transcriptional expression of PDHB and the risk of local recurrence in patients with oral cavity carcinomas. MethodsWe determined the transcriptional expression of PDHB in biopsies from 41 patients with oral cavity carcinomas treated with surgery. The PDHB expression was categorized according to the local control of the disease with a recursive partitioning analysis. ResultsDuring the follow-up period 13 patients (31.7%) had a local recurrence of the tumor. Considering local disease control as the dependent variable, the recursive partitioning analysis classified the patients in two categories according to high (n=16, 39.0%) or low (n=25, 61.0%) PDHB expression. Five-year local recurrence-free survival for patients with high PDHB expression was 84.8% (95% CI: 65.2-100%), and for patients with low expression it was 54.3% (95% CI: 34.3–74.2 %) (P=0.034). The results of multivariate analysis showed that patients with a low PDHB expression had a 4.90 times higher risk of local recurrence of the tumor (95% CI: 1.02–22.68, P=0.042). ConclusionThere is a relationship between the metabolic characteristics of the tumor and its aggressiveness. According to our results, patients with oral cavity carcinomas with low transcriptional expression levels of PDHB have a significantly higher risk of local tumor recurrence.

Treatment effect of remdesivir on the mortality of hospitalised COVID-19 patients in Switzerland across different patient groups: a tree-based model analysis.

Remdesivir has shown benefits against COVID-19. However, it remains unclear whether, to what extent, and among whom remdesivir can reduce COVID-19-related mortality. We explored whether the treatment response to remdesivir differed by patient characteristics. We analysed data collected from a hospital surveillance study conducted in 21 referral hospitals in Switzerland between 2020 and 2022. We applied model-based recursive partitioning to group patients by the association between treatment levels and mortality. We included either treatment (levels: none, remdesivir within 7 days of symptom onset, remdesivir after 7 days, or another treatment), age and sex, or treatment only as regression variables. Candidate partitioning variables included a range of risk factors and comorbidities (and age and sex unless included in regression). We repeated the analyses using local centring to correct the results for the propensity to receive treatment. Overall (n = 21,790 patients), remdesivir within 7 days was associated with increased mortality (adjusted hazard ratios 1.28-1.54 versus no treatment). The CURB-65 score caused the most instability in the regression parameters of the model. When adjusted for age and sex, patients receiving remdesivir within 7 days of onset had higher mortality than those not treated in all identified eight patient groups. When age and sex were included as partitioning variables instead, the number of groups increased to 19-20; in five to six of those branches, mortality was lower among patients who received early remdesivir. Factors determining the groups where remdesivir was potentially beneficial included the presence of oncological comorbidities, male sex, and high age. Some subgroups of patients, such as individuals with oncological comorbidities or elderly males, may benefit from remdesivir.

Sex-Specific Implant Fixation Can Reduce Revision Rates in Total Hip Arthroplasty: Evidence From the Swiss National Joint Registry

BackgroundPatient’s sex is considered a risk factor for revision following primary total hip arthroplasty (THA), but sex-specific treatment guidelines are lacking. The purpose was to assess sex-specificity of risk factors for periprosthetic femoral fractures (PFFs) and aseptic stem loosening (ASL) in a nationwide register study. MethodsAll uncemented and hybrid THAs for hip osteoarthritis registered in the Swiss National Joint Registry were considered. 86,423 THAs were analyzed. Comparable THA subsets for both sexes were obtained through propensity score matching (1:1). A sex-specific analysis of risk factors for early PFF or ASL was performed using recursive partitioning analyses. ResultsIn women, PFFs were most significantly associated with uncemented THA fixation (P < .0001) and age (P < .01, threshold: 70.5 years). The ASLs were solely associated with patient age of <65 years (P = .023). In men, PFFs were associated exclusively with an American Society of Anesthesiologists (ASA) score >2 (P = .026). The ASLs were not correlated to any of the potential risk factors analyzed. A mathematical simulation indicated that avoiding uncemented THA fixation in women ≥70.5 years of age decreased the number of revisions within the observational period by 21% in this subset and by 4.9% in the entire patient population. ConclusionUncemented THA should be avoided in women >70.5 years due to the increased risk of early PFF, while the mode of stem fixation did not influence revision risk in men. A sex-specific regimen for THA fixation has the potential to markedly reduce early THA revision rates.

Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma

BackgroundSeveral researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection. MethodsThe data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC). ResultsThe RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication. ConclusionThe present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.

Identifying Predictors of First-Line Subcutaneous TNF-Inhibitor Persistence in Patients with Inflammatory Arthritis: A Decision Tree Analysis by Indication.

Treatment persistence is a proxy for efficacy, safety and patient satisfaction, and a switch in treatment or treatment discontinuation has been associated with increased indirect and direct costs in inflammatory arthritis (IA). Hence, there are both clinical and economic incentives for the identification of factors associated with treatment persistence. Until now, studies have mainly leveraged traditional regression analysis, but it has been suggested that novel approaches, such as statistical learning techniques, may improve our understanding of factors related to treatment persistence. Therefore, we set up a study using nationwide Swedish high-coverage administrative register data with the objective to identify patient groups with distinct persistence of subcutaneous tumor necrosis factor inhibitor (SC-TNFi) treatment in IA, using recursive partitioning, a statistical learning algorithm. IA was defined as a diagnosis of rheumatic arthritis (RA), ankylosing spondylitis/unspecified spondyloarthritis (AS/uSpA) or psoriatic arthritis (PsA). Adult swedish biologic-naïve patients with IA initiating biologic treatment with a SC-TNFi (adalimumab, etanercept, certolizumab or golimumab) between May 6, 2010, and December 31, 2017. Treatment persistence of SC-TNFi was derived based on prescription data and a defined standard daily dose. Patient characteristics, including age, sex, number of health care contacts, comorbidities and treatment, were collected at treatment initiation and 12months before treatment initiation. Based on these characteristics, we used recursive partitioning in a conditional inference framework to identify patient groups with distinct SC-TNFi treatment persistence by IA diagnosis. A total of 13,913 patients were included. Approximately 50% had RA, while 27% and 23% had AS/uSpA and PsA, respectively. The recursive partitioning algorithm identified sex and treatment as factors associated with SC-TNFi treatment persistence in PsA and AS/uSpA. Time on treatment in the groups with the lowest treatment persistence was similar across all three indications (9.5-11.3months), whereas there was more variation in time on treatment across the groups with the highest treatment persistence (18.4-48.9months). Women have low SC-TNFi treatment persistence in PsA and AS/uSpA whereas male sex and golimumab are associated with high treatment persistence in these indications. The factors associated with treatment persistence in RA were less distinct but may comprise disease activity and concurrent conventional systemic disease-modifying anti-rheumatic drug (DMARD) treatment.

Stratifying Risk of Nonadherence in Lingual Strengthening Dysphagia Rehabilitation.

Exercise-based treatments may improve swallowing safety and efficiency; yet, it is not clearly understood which factors predict nonadherence to recommended treatment protocols. The aim of this study was to construct an algorithm for stratifying risk of nonadherence to a lingual strengthening dysphagia treatment program. Using recursive partitioning, we created a classification tree built from a pool of sociodemographic, clinical, and functional status indicators to identify risk groups for nonadherence to an intensive lingual strengthening treatment program. Nonadherence, or noncompletion, was defined as not completing two or more follow-up sessions or a final session within 84 days. The study cohort consisted of 243 Veterans enrolled in the Intensive Dysphagia Treatment program across six sites from January 2012 to August 2019. The overall rate of nonadherence in this cohort was 38%. The classification tree demonstrated good discriminate validity (C-statistic = 0.74) and contained eight groups from five variables: primary diagnosis, marital status, Penetration-Aspiration Scale (PAS) severity score, race/ethnicity, and age. Nonadherence risk was categorized as high (range: 69%-77%), intermediate (27%-33%), and low risk (≤ 13%-22%). This study identified distinct risk groups for nonadherence to lingual strengthening dysphagia rehabilitation. Additional research is necessary to understand how these factors may drive nonadherence. With external validation and refinement through prospective studies, a clinically relevant risk stratification tool can be developed to identify patients who may be at high risk for nonadherence and provide targeted patient support to mitigate risk and provide for unmet needs.

Capacidad predictiva de la expresión transcripcional de FAT1 en pacientes con carcinomas escamosos de cabeza y cuello tratados con radioterapia

ObjectiveTo analyze the predictive capacity at the primary location of the tumor of the FAT1 transcriptional expression in patients with head and neck squamous cell carcinoma treated with radiotherapy. Material and methodsWe conducted a retrospective study from biopsies of the primary location of the tumor in 82 patients with head and neck squamous cell carcinoma treated with radiotherapy. The transcriptional expression of FAT1 was determined by RT-PCR. The level of FAT1 transcriptional expression was categorized according to the local control after radiotherapy using a recursive partitioning analysis. ResultsElevated FAT1 transcriptional expression was associated with an increased risk of local recurrence after radiotherapy. Patients with a high expression level of FAT1 (n=18; 22.0%) had a 5-year local recurrence-free survival of 42.1% (95% CI: 18.6–65.6%), whereas for patients with a low expression (n=64; 78.0%) it was 72.4% (95% CI: 61.5%–83.3%) (P=0.002). According to the result of a multivariate analysis, patients with a high FAT1 expression category had a 2.3-fold increased risk of local recurrence (95% CI: 1.0–5.2; P=0.043). ConclusionsElevated FAT1 transcriptional expression was associated with a significantly increased risk of local recurrence in patients with head and neck squamous cell carcinoma treated with radiotherapy.

Brain metastasis resection: the impact of fluorescence guidance (MetResect study).

Maximal resection of brain metastases (BMs) improves both progression-free survival and overall survival (OS). Fluorescein sodium (FL) in combination with the YELLOW 560-nm filter is a safe and feasible method for visualizing residual tumor tissue during BM resection. The authors of this study aimed to show that use of FL would positively influence the volumetric extent of resection (EOR) and thus the survival outcome in patients undergoing BM resection. Analyzing their institution's prospective brain tumor registry, the authors identified 539 consecutive patients with BMs (247 women, mean age 62.8 years) by using preoperative high-quality MR images for volumetric analysis. BMs were resected under white light (WL) in 293 patients (54.4%; WL group) and under FL guidance in 246 patients (45.6%; FL group). Sex, age, presurgical Karnofsky Performance Status (KPS), recursive partitioning analysis class, and adjuvant treatment modalities were well balanced between the two groups. Volumetric analysis was performed in a blinded fashion by quantifying pre- and postoperative tumor volume based on gadolinium-enhanced T1-weighted sequences. In the FL group, the postoperative tumor volume was significantly smaller (p = 0.01), and hence the quantitative EOR was significantly larger (p = 0.024) and OS was significantly longer (p = 0.0001) (log-rank testing). Multivariate Cox regression modeling showed that age, presurgical KPS, metastasis status, and FL-guided resection are independent prognostic factors for survival. Compared with WL resection, FL-guided BM resection increased resection quality, significantly improved EOR, and prolonged OS.

Prognostic implication of pre-transplant FEV1 on long-term outcomes following allogeneic hematopoietic stem cell transplantation.

Pre-transplant pulmonary function testing (PFT) is essential before allogeneic hematopoietic stem cell transplant (HCT), yet the optimal cutoff value for affecting transplant outcomes remains poorly defined. Retrospective analysis of pre-HCT PFT data from 605 consecutive patients at the Princess Margaret Cancer Centre between January 1, 2004 and December 31, 2013 used binary recursive partitioning to identify cutoff values for overall survival (OS) as an endpoint of transplant outcomes. These values were compared to HCT comorbidity index (HCT-CI) FEV1 cutoffs for OS, cumulative incidence of relapse and non-relapse mortality. FEV1 ≥ 81% was the identified cutoff point. The OS rate at 3 years showed 49.8% (FEV1 ≥ 81%) vs. 36.6% (<81%, p < .001). For HCT-CI cutoffs, the OS rate at 3 years for FEV1 ≥ 80%, 66%-80% and ≤65% were 49.0%, 38.1% and 37.6% (p = .011), respectively. Multivariate analysis confirmed that FEV1 ≥ 81% predicted reduced mortality (HR 0.682, p = .001). Subgroup analysis showed both FEV1 ≥ 81% and FEV1 by HCT-CI cutoffs may stratify patients according to OS and NRM risk in subgroups receiving myeloablative, but not reduced intensity conditioning. FEV1 ≥ 81% can predict OS and NRM in our cohort and is potentially simpler when risk stratifying patients undergoing allogeneic HCT, particularly those receiving myeloablative conditioning.

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

BackgroundIn Sarawak, 252 300 coronavirus disease 2019 (COVID-19) cases have been recorded with 1 619 fatalities in 2021, compared to only 1 117 cases in 2020. Since Sarawak is geographically separated from Peninsular Malaysia and half of its population resides in rural districts where medical resources are limited, the analysis of spatiotemporal heterogeneity of disease incidence rates and their relationship with socio-demographic factors are crucial in understanding the spread of the disease in Sarawak.MethodsThe spatial dependence of district-wise incidence rates is investigated using spatial autocorrelation analysis with two orders of contiguity weights for various pandemic waves. Nine determinants are chosen from 14 covariates of socio-demographic factors via elastic net regression and recursive partitioning. The relationships between incidence rates and socio-demographic factors are examined using ordinary least squares, spatial lag and spatial error models, and geographically weighted regression.ResultsIn the first 8 months of 2021, COVID-19 severely affected Sarawak’s central region, which was followed by the southern region in the next 2 months. In the third wave, based on second-order spatial weights, the incidence rate in a district is most strongly influenced by its neighboring districts’ rate, although the variance of incidence rates is best explained by local regression coefficient estimates of socio-demographic factors in the first wave. It is discovered that the percentage of households with garbage collection facilities, population density and the proportion of male in the population are positively associated with the increase in COVID-19 incidence rates.ConclusionThis research provides useful insights for the State Government and public health authorities to critically incorporate socio-demographic characteristics of local communities into evidence-based decision-making for altering disease monitoring and response plans. Policymakers can make well-informed judgments and implement targeted interventions by having an in-depth understanding of the spatial patterns and relationships between COVID-19 incidence rates and socio-demographic characteristics. This will effectively help in mitigating the spread of the disease.

Establishment of a prognostic risk prediction modelfor non-small cell lung cancer patients with brainmetastases: a retrospective study.

Patients with non-small cell lung cancer (NSCLC) who develop brain metastases (BM) have a poor prognosis. This study aimed to construct a clinical prediction model to determine the overall survival (OS) of NSCLC patients with BM. A total of 300 NSCLC patients with BM at the Yunnan Cancer Centre were retrospectively analysed. The prediction model was constructed using the least absolute shrinkage and selection operator-Cox regression. The bootstrap sampling method was employed for internal validation. The performance of our prediction model was compared using recursive partitioning analysis (RPA), graded prognostic assessment (GPA), the update of the graded prognostic assessment for lung cancer using molecular markers (Lung-molGPA), the basic score for BM (BSBM), and tumour-lymph node-metastasis (TNM) staging. The prediction models comprising 15 predictors were constructed. The area under the curve (AUC) values for the 1-year, 3-year, and 5-year time-dependent receiver operating characteristic (curves) were 0.746 (0.678-0.814), 0.819 (0.761-0.877), and 0.865 (0.774-0.957), respectively. The bootstrap-corrected AUC values and Brier scores for the prediction model were 0.811 (0.638-0.950) and 0.123 (0.066-0.188), respectively. The time-dependent C-index indicated that our model exhibited significantly greater discrimination compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging. Similarly, the decision curve analysis demonstrated that our model displayed the widest range of thresholds and yielded the highest net benefit. Furthermore, the net reclassification improvement and integrated discrimination improvement analyses confirmed the enhanced predictive power of our prediction model. Finally, the risk subgroups identified by our prognostic model exhibited superior differentiation of patients' OS. The clinical prediction model constructed by us shows promise in predicting OS for NSCLC patients with BM. Its predictability is superior compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging.

Using Proteome Microarray and Gene Expression Omnibus Database to Screen Tumour-Associated Antigens to Construct the Optimal Diagnostic Model of Oesophageal Squamous Cell Carcinoma

AimsAutoantibodies against tumour-associated antigens (TAAs) are promising biomarkers for early immunodiagnosis of cancers. This study was designed to screen and verify autoantibodies against TAAs in sera as diagnostic biomarkers for oesophageal squamous cell carcinoma (ESCC). Materials and methodsThe customised proteome microarray based on cancer driver genes and the Gene Expression Omnibus database were used to identify potential TAAs. The expression levels of the corresponding autoantibodies in serum samples obtained from 243 ESCC patients and 243 healthy controls were investigated by enzyme-linked immunosorbent assay (ELISA). In total, 486 serum samples were randomly divided into the training set and the validation set in the ratio of 2:1. Logistic regression analysis, recursive partition analysis and support vector machine were performed to establish different diagnostic models. ResultsFive and nine candidate TAAs were screened out by proteome microarray and bioinformatics analysis, respectively. Among these 14 anti-TAAs autoantibodies, the expression level of nine (p53, PTEN, GNA11, SRSF2, CXCL8, MMP1, MSH6, LAMC2 and SLC2A1) anti-TAAs autoantibodies in the cancer patient group was higher than that in the healthy control group based on the results from ELISA. In the three constructed models, a logistic regression model including four anti-TAA autoantibodies (p53, SLC2A1, GNA11 and MMP1) was considered to be the optimal diagnosis model. The sensitivity and specificity of the model in the training set and the validation set were 70.4%, 72.8% and 67.9%, 67.9%, respectively. The area under the receiver operating characteristic curve for detecting early patients in the training set and the validation set were 0.84 and 0.85, respectively. ConclusionsThis approach to screen novel TAAs is feasible, and the model including four autoantibodies could pave the way for the diagnosis of ESCC.

Exploring molecular fingerprints of different drugs having bile interaction: a stepping stone towards better drug delivery.

Bile acids are amphiphilic substances produced naturally in humans. In the context of drug delivery and dosage form design, it is critical to understand whether a drug interacts with bile inside the gastrointestinal (GI) tract or not. This study focuses on the identification of structural fingerprints/features important for bile interaction. Molecular modelling methods such as Bayesian classification and recursive partitioning (RP) studies are executed to find important fingerprints/features for the bile interaction. For the Bayesian classification study, the ROC score of 0.837 and 0.950 are found for the training set and the test set compounds, respectively. The fluorine-containing aliphatic/aromatic group, the branched chain of the alkyl group containing hydroxyl moiety and the phenothiazine ring etc. are identified as good fingerprints having a positive contribution towards bile interactions, whereas, the bad fingerprints such as free carboxylate group, purine, and pyrimidine ring etc. have a negative contribution towards bile interactions. The best tree (tree ID: 1) from the RP study classifies the bile interacting or non-interacting compounds with a ROC score of 0.941 for the training and 0.875 for the test set. Additionally, SARpy and QSAR-Co analyses are also been performed to classify compounds as bile interacting/non-interacting. Moreover, forty-six recently FDA-approved drugs have been screened by the developed SARpy and QSAR-Co models to assess their bile interaction properties. Overall, this attempt may facilitate the researchers to identify bile interacting/non-interacting molecules in a faster way and help in the design of formulations and target-specific drug development.

Post-Surgical Prognosis of Patients with Pineoblastoma: A Systematic Review and Individual Patient Data Analysis with Trends over Time

Most of the literature on pineoblastoma consists of case reports and single-institution series. The goal of this systematic review and individual patient data (IPD) analysis was to summarize the existing literature, identify factors associated with overall survival (OS), and provide a contemporary update on prognosis for patients with pineoblastoma. Forty-four studies were identified with 298 patients having IPD. Kaplan–Meier analyses were used to report survival outcomes based on age, tumor metastases, extent of resection (EOR), adjuvant therapy, and publication year. Cox regression was performed to identify independent predictors of time to mortality. Multivariable recursive partitioning analysis was used to identify the most important subgroups associated with mortality. Patients were classified based on publication year before and after the last systematic review on this topic (pre-2012 and 2012 onwards) and compared using univariate and multivariable analyses. This study demonstrates that EOR less-than-gross total resection, metastatic presentation, adjuvant chemotherapy without radiation, and tumor presentation in children less than three years old are associated with poorer prognosis. Since 2012, the 5-year actuarial OS has improved from 32.8% to 56.1%, which remained significant even after accounting for EOR, age, and adjuvant therapy. Pineoblastoma remains a severe rare disease, but survival outcomes are improving.

A Comparative Analysis of Data Mining Methods and Hierarchical Linear Modeling Using PISA 2018 Data

A Comparative Analysis of Data Mining Methods and Hierarchical Linear Modeling Using PISA 2018 Data

Prognostic model on overall survival in elderly nasopharyngeal carcinoma patients: a recursive partitioning analysis identifying pre-treatment risk stratification

BackgroundWe aimed to evaluate the optimal management for elderly patients with nasopharyngeal carcinoma (NPC) with intensity-modulated radiotherapy (IMRT).MethodsA total of 283 elderly patients with NPC diagnosed from 2015 to 2019 were enrolled in the study. Overall survival (OS) was the primary endpoint. Univariate and multivariate Cox regression analyses were preformed to identify potential prognostic factors. The recursive partitioning analysis (RPA) was used for risk stratification. Kaplan-Meier survival curves were applied to evaluate the survival endpoints, and log-rank test was utilized to assess differences between groups. The prognostic index (PI) was constructed to further predict patients’ prognosis displayed by nomogram model. The area under the receiver operating characteristic (ROC) curves (AUC) and the calibration curves were applied to assess the effectiveness of the model.ResultsBased on RPA-based risk stratification, we demonstrated that elderly NPC patients who were treated with IC followed by RT had similar OS as those with induction chemotherapy (IC) combined with concurrent chemoradiotherapy (CCRT) in the middle- (stage I-III and pre-treatment EBV > 1840 copies/ml) and high-risk groups (stage IVA). IMRT alone may be the optimal treatment option for the low-risk group (stage I-III with pre-treatment EBV ≤ 1840 copies/ml). We established an integrated PI which was indicted with stronger prognostic power than each of the factors alone for elderly NPC patients (The AUC of PI was 0.75, 0.80, and 0.82 for 1-, 3-, 5-year prediction of OS, respectively).ConclusionWe present a robust model for clinical stratification which could guide individual therapy for elderly NPC patients.

Comparative impact of grade on mortality across salivary cancers: A novel, unifying staging system.

The comparative impact of histologic variants and grade has not been well described. Salivary cancer histologies were profiled using hospital and population-based cancer registries. Multivariable models were employed to assess relationships between histology, grade, and survival. On univariate analysis, histologic variants exhibited a wide spectrum of mortality risk (5-year overall survival (OS): 86% (acinic cell carcinoma), 78% (mucoepidermoid carcinoma), 72% (adenoid cystic carcinoma), 64% (carcinoma ex-pleomorphic adenoma), 52% (adenocarcinoma NOS), and 47% (salivary duct carcinoma) (p < 0.001). However, on multivariable analysis these differences largely vanished. Worsening grade corresponded with deteriorating survival (5-year OS: 89% [low-grade], 81% [intermediate-grade], 45% [high-grade]; p < 0.001), which was upheld on multivariable analysis and propensity score matching. Recursive partitioning analysis generated TNM + G schema (c-index 0.75) superior to the existing system (c-index 0.73). Grade represents a primary determinant of salivary cancer prognosis. Integrating grade into stage strengthens current staging systems.

Predictive Roles of Baseline Stromal Tumor-Infiltrating Lymphocytes and Ki-67 in Pathologic Complete Response in an Early-Stage Triple-Negative Breast Cancer Prospective Trial

High stromal tumor-infiltrating lymphocytes (sTILs) are associated with improved pathologic complete response (pCR) in triple-negative breast cancer (TNBC). We hypothesize that integrating high sTILs and additional clinicopathologic features associated with pCR could enhance our ability to predict the group of patients on whom treatment de-escalation strategies could be tested. In this prospective early-stage TNBC neoadjuvant chemotherapy study, pretreatment biopsies from 408 patients were evaluated for their clinical and demographic features, as well as biomarkers including sTILs, Ki-67, PD-L1 and androgen receptor. Multivariate logistic regression models were developed to generate a computed response score to predict pCR. The pCR rate for the entire cohort was 41%. Recursive partitioning analysis identified ≥20% as the optimal cutoff for sTILs to denote 35% (143/408) of patients as having high sTILs, with a pCR rate of 59%, and 65% (265/408) of patients as having low sTILs, with a pCR rate of 31%. High Ki-67 (cutoff &gt; 35%) was identified as the only predictor of pCR in addition to sTILs in the training set. This finding was verified in the testing set, where the highest computed response score encompassing both high sTILa and high Ki-67 predicted a pCR rate of 65%. Integrating Ki67 and sTIL may refine the selection of early stage TNBC patients for neoadjuvant clinical trials evaluating de-escalation strategies.

Relevance of the Updated Recursive Partitioning Analysis (U-RPA) Classification in the Contemporary Care of Patients with Brain Metastases.

Patients with brain metastases (BMETS) need information about the prognosis and potential value of treatment options to make informed therapeutic decisions, but tools to predict survival in contemporary practice are scarce. We propose an Updated Recursive Partitioning Analysis (U-RPA) instrument to predict survival and benefit from brain-directed treatment (BDT) of contemporary patients. This was a retrospective analysis of patients with BMETS treated between 2017 and 2019. With survival as the primary endpoint, we calculated the U-RPA and generated estimates using Kaplan-Meier curves and hazard ratios. Of 862 eligible patients, 752 received BDT and 110 received best supportive care (BSC). Median overall survival with BDT and BSC was 9.3 and 1.3 months, respectively. Patients in RPA class 1, 2A, 2B and 3 who underwent BDT had median survival of 28.1, 14.7, 7.6 and 3.3 months, respectively. The median survival for patients in RPA 3 who received BDT (n = 147), WBRT (n = 79) and SRS (n = 54) was 3.3, 2.9 and 4.1 months, respectively. The U-RPA defines prognosis estimates, independent of tumor type and treatment modality, which can assist to make value-based care treatment decisions. The prognosis for patients in U-RPA class 2B and 3 remains poor, with consideration for early palliative care involvement in these cases.