Development and Validation of a Predictive Model for Acute Kidney Injury in Sepsis Patients Based on Recursive Partition Analysis

BACKGROUND

Sepsis-associated acute kidney injury (SA-AKI) is a critical condition with significant clinical implications, yet there is a need for a predictive model that can reliably assess the risk of its development. This study is undertaken to bridge a gap in healthcare by creating a predictive model for SA-AKI with the goal of empowering healthcare providers with a tool that can revolutionize patient care and ultimately lead to improved outcomes.

METHODS

A cohort of 615 patients afflicted with sepsis, who were admitted to the intensive care unit, underwent random stratification into 2 groups: a training set (n = 435) and a validation set (n = 180). Subsequently, a multivariate logistic regression model, imbued with nonzero coefficients via LASSO regression, was meticulously devised for the prognostication of SA-AKI. This model was thoughtfully rendered in the form of a nomogram. The salience of individual risk factors was assessed and ranked employing Shapley Additive Interpretation (SHAP). Recursive partition analysis was performed to stratify the risk of patients with sepsis.

RESULTS

Among the panoply of clinical variables examined, hypertension, diabetes mellitus, C-reactive protein, procalcitonin (PCT), activated partial thromboplastin time, and platelet count emerged as robust and independent determinants of SA-AKI. The receiver operating characteristic curve analysis for SA-AKI risk discrimination in both the training set and validation set yielded an area under the curve estimates of 0.843 (95% CI: 0.805 to 0.882) and 0.834 (95% CI: 0.775 to 0.893), respectively. Notably, PCT exhibited the most conspicuous influence on the model's predictive capacity. Furthermore, statistically significant disparities were observed in the incidence of SA-AKI and the 28-day survival rate across high-risk, medium-risk, and low-risk cohorts (P < .05).

CONCLUSION

The composite predictive model, amalgamating the quintet of SA-AKI predictors, holds significant promise in facilitating the identification of high-risk patient subsets.

Construction of refined staging classification systems integrating FIGO/T-categories and corpus uterine invasion for non-metastatic cervical cancer

BACKGROUND

To investigate the prognostic value of corpus uterine invasion (CUI) in cervical cancer (CC), and determine the necessity to incorporate it for staging.

METHODS

A total of 809 cases of biopsy-proven, non-metastatic CC were identified from an academic cancer center. Recursive partitioning analysis (RPA) method was used to develop the refined staging systems with respect to overall survival (OS). Internal validation was performed by using calibration curve with 1000 bootstrap resampling. Performances of the RPA-refined stages were compared against the conventional FIGO 2018 and 9th edition TNM-stage classifications by the receiver operating characteristic curve (ROC) and decision curve analysis (DCA).

RESULTS

We identified that CUI was independently prognostic for death and relapse in our cohort. RPA modeling using a two-tiered stratification by CUI (positive and negative) and FIGO/T-categories divided CC into three risk groupings (FIGO I'-III'/T1'-3'), with 5-year OS of 90.8%, 82.1%, and 68.5% for proposed FIGO stage I'-III', respectively (p ≤ 0.003 for all pairwise comparisons), and 89.7%, 78.8%, and 68.0% for proposed T1'-3', respectively (p < 0.001 for all pairwise comparisons). The RPA-refined staging systems were well validated with RPA-predicted OS rates showed optimal agreement with actual observed survivals. Additionally, the RPA-refined stages outperformed the conventional FIGO/TNM-stage with significantly higher accuracy of survival prediction (AUC: RPA-FIGO vs. FIGO, 0.663 [95% CI 0.629-0.695] vs. 0.638 [0.604-0.671], p = 0.047; RPA-T vs. T, 0.661 [0.627-0.694] vs. 0.627 [0.592-0.660], p = 0.036).

CONCLUSION

CUI affects the survival outcomes in patients with CC. Disease extended to corpus uterine should be classified as stage III/T3.

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.

Clinical utility of pretreatment serum squamous cell carcinoma antigen for prognostication and decision-making in patients with early-stage cervical cancer

Background

To investigate the prognostic role of pretreatment squamous cell carcinoma antigen (SCCA) in early-stage cervical cancer (CC).

Methods

We enrolled 487 cases of pathology-proven early-stage [International Federation of Gynecology and Obstetrics (FIGO) I/II] squamous or adenosquamous CC that were treated from 2012 to 2015. Restricted cubic splines (RCS) with a full Cox regression model were used to evaluate the association between SCCA levels and survival outcomes. Recursive partitioning analysis (RPA) was used to construct a risk stratification model for overall survival (OS). The performance of the RPA-based model was assessed using a receiver operating characteristic (ROC) curve.

Results

RCS analysis revealed an association between SCCA and OS and disease-free survival (DFS); SCCA ⩾2.5 ng/mL was robust for risk discrimination in our cohort. SCCA had an interaction effect with FIGO classification: Patients with FIGO I and SCCA ⩾2.5 ng/mL overlapped with those with FIGO II and SCCA < 2.5 ng/mL for OS [hazard ratio, 1.04 (95% confidence interval (CI): 0.49-2.24), p = 0.903] and DFS [1.05 (0.56-1.98), p = 0.876]. RPA modeling incorporating SCCA (<2.5 ng/mL and ⩾2.5 ng/mL) and FIGO classification divided CC into three prognostic groups: RPA I, FIGO stage I, and SCCA < 2.5 ng/mL; RPA II, FIGO stage I, and SCCA ⩾ 2.5 ng/mL, or FIGO stage II and SCCA < 2.5 ng/mL; and RPA III, FIGO stage II, and SCCA ⩾ 2.5 ng/mL; with 5-year OS of 94.0%, 85.1%, and 73.5%, respectively (p < 0.001). ROC analysis confirmed that the RPA model outperformed the FIGO 2018 stage with significantly improved accuracy for survival prediction [area under the curve: RPA versus FIGO, 0.663 (95% CI: 0.619-0.705] versus 0.621 (0.576-0.664), p = 0.045]. Importantly, the RPA groupings were associated with the efficacy of treatment regimens. Surgery followed by adjuvant treatment had a higher OS (p < 0.01) and DFS (p = 0.024) than other treatments for RPA III, whereas outcomes were comparable among treatment regimens for RPA I-II.

Conclusion

Herein, the role of SCCA for prognostication was confirmed, and a robust clinicomolecular risk stratification system that outperforms conventional FIGO classification in early-stage squamous and adenosquamous CC was presented. The model correlated with the efficacy of different treatment regimes.

Identification of Atezolizumab Plus Bevacizumab Prognostic Index via Recursive Partitioning Analysis in HCC: The ABE Index

BACKGROUND/AIM

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.

PATIENTS AND METHODS

A total of 784 patients with HCC were included in the analysis.

RESULTS

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%).

CONCLUSION

The ABE index allows for easy stratification of HCC patients treated with the combination of ABE in first-line setting.

A modified mTNM staging system based on lymph node ratio for colon neuroendocrine tumors: A recursive partitioning analysis

BACKGROUND

In the current tumor-lymph node-metastasis (TNM) staging system for colon neuroendocrine tumors, lymph node status is divided into N1 and N0. An assessment of the lymph node ratio (LNR) and a proposal for a modified mTNM staging system were the objectives of this study.

METHODS

Selecting the optimal cut-off value of LNR was done using X-tile. A Cox regression model and the Kaplan-Meier method were performed to calculate patient cancer-specific survival in the Surveillance, Epidemiology and End Results cohort. Recursive partitioning analysis was used to improve TNM staging.

RESULTS

The study included 674 patients. The current TNM staging system showed inadequate discriminatory power between stage I and stage II patients (p = 0.088). The optimal cut-off value was determined as 0.6 for LNR. Based on multivariate Cox regression analysis, the modified mN classification could be classified into mN 0 (LNR = 0.00), mN 1 (LNR = 0.01-0.60), and mN 2 (LNR > 0.60), and was found to be an independent factor affecting prognosis (p < 0.001). Using the American Joint Committee on Cancer T and modified mN classifications, the modified mTNM system was constructed, and it exhibited better prognostic discriminatory power ability than the traditional TNM system (C-index: 0.587 vs. 0.665).

CONCLUSIONS

Our study determined that LNR is a prognostic factor in colon NET patients. In addition, to more accurately assess the prognosis of colon NET patients, we proposed a modified mTNM staging system.

An Exploratory Study of Refining TNM-8 M1 Categories and Prognostic Subgroups Using Plasma EBV DNA for Previously Untreated De Novo Metastatic Nasopharyngeal Carcinoma

(1) Background: NPC patients with de novo distant metastasis appears to be a heterogeneous group who demonstrate a wide range of survival, as suggested by growing evidence. Nevertheless, the current 8th edition of TNM staging (TNM-8) grouping all these patients into the M1 category is not able to identify their survival differences. We sought to identify any anatomic and non-anatomic subgroups in this study. (2) Methods: Sixty-nine patients with treatment-naive de novo M1 NPC (training cohort) were prospectively recruited from 2007 to 2018. We performed univariable and multivariable analyses (UVA and MVA) to explore anatomic distant metastasis factors, which were significantly prognostic of overall survival (OS). Recursive partitioning analysis (RPA) with the incorporation of significant factors from MVA was then performed to derive a new set of RPA stage groups with OS segregation (Set 1 Anatomic-RPA stage groups); another run of MVA was performed with the addition of pre-treatment plasma EBV DNA. A second-round RPA with significant prognostic factors of OS identified in this round of MVA was performed again to derive another set of stage groups (Set 2 Prognostic-RPA stage groups). Both sets were then validated externally with an independent validation cohort of 67 patients with distant relapses of their initially non-metastatic NPC (rM1) after radical treatment. The performance of models in survival segregation was evaluated by the Akaike information criterion (AIC) and concordance index (C-index) under 1000 bootstrapping samples for the validation cohort; (3) Results: The 3-year OS and median follow-up in the training cohort were 36.0% and 17.8 months, respectively. Co-existence of liver-bone metastases was the only significant prognostic factor of OS in the first round UVA and MVA. Set 1 RPA based on anatomic factors that subdivide the M1 category into two groups: M1a (absence of co-existing liver-bone metastases; median OS 28.1 months) and M1b (co-existing liver-bone metastases; median OS 19.2 months, p = 0.023). When pre-treatment plasma EBV DNA was also added, it became the only significant prognostic factor in UVA (p = 0.001) and MVA (p = 0.015), while co-existing liver-bone metastases was only significant in UVA. Set 2 RPA with the incorporation of pre-treatment plasma EBV DNA yielded good segregation (M1a: EBV DNA ≤ 2500 copies/mL and M1b: EBV DNA > 2500 copies/mL; median OS 44.2 and 19.7 months, respectively, p < 0.001). Set 2 Prognostic-RPA groups (AIC: 228.1 [95% CI: 194.8−251.8] is superior to Set 1 Anatomic-RPA groups (AIC: 278.5 [254.6−301.2]) in the OS prediction (p < 0.001). Set 2 RPA groups (C-index 0.59 [95% CI: 0.54−0.67]) also performed better prediction agreement in the validation cohort (vs. Set 1: C-index 0.47 [95% CI: 0.41−0.53]) (p < 0.001); (4) Conclusions: Our Anatomic-RPA stage groups yielded good segregation for de novo M1 NPC, and prognostication was further improved by incorporating plasma EBV DNA. These new RPA stage groups for M1 NPC can be applied to countries/regions regardless of whether reliable and sensitive plasma EBV DNA assays are available or not.

Risk stratification after recurrence of human papillomavirus (HPV)-related and non-HPV-related oropharyngeal cancer: A secondary analysis of NRG Oncology RTOG 0129 and 0522

BACKGROUND

No risk-stratification strategies exist for patients with recurrent oropharyngeal cancer (OPC).

METHODS

Retrospective analysis using data from prospective NRG Oncology clinical trials RTOG 0129 and 0522. Eligibility criteria included known p16 status and smoking history, and locoregional/distant recurrence. Overall survival (OS) was measured from date of recurrence. Recursive partitioning analysis was performed to produce mutually exclusive risk groups.

RESULTS

Hundred and fifty-four patients were included with median follow-up after recurrence of 3.9 years (range 0.04-9.0). The most important factors influencing survival were p16 status and type of recurrence, followed by surgical salvage and smoking history (≤20 vs. >20 pack-years). Three significantly different risk groups were identified. Patients in the low-, intermediate-, and high-risk groups had 2-year OS after recurrence of 81.1% (95%CI 68.5-93.7), 50.2% (95%CI 36.0-64.5), and 20.8% (95%CI 10.5-31.1), respectively.

CONCLUSION

Patient and tumor characteristics may be used to stratify patients into risk groups at the time of OPC recurrence.

Diagnostic models for impending death in terminally ill cancer patients: A multicenter cohort study

Background

Accurately predicting impending death is essential for clinicians to clarify goals of care. We aimed to develop diagnostic models to predict death ≤3 days in cancer patients.

Methods

In this multicenter cohort study, we consecutively enrolled advanced cancer patients admitted to 23 inpatient hospices in 2017. Fifteen clinical signs related to impending death were documented daily from the day when the Palliative Performance Scale (PPS) declined to ≤20–14 days later. We conducted recursive partitioning analysis using the entire data set and performed cross‐validation to develop the model (prediction of 3‐day impending death‐decision tree [P3did‐DT]). Then, we summed the number of systems (nervous/cardiovascular/respiratory/musculoskeletal), where any sign was present to underpin P3did score (range = 0–4).

Results

Data following PPS ≤20 were obtained from 1396 of 1896 inpatients (74%). The mean age was 73 ± 12 years, and 399 (29%) had gastrointestinal tract cancer. The P3did‐DT was based on three variables and had four terminal leaves: urine output (u/o) ≤200 ml/day and decreased response to verbal stimuli, u/o ≤200 ml/day and no decreased response to verbal stimuli, u/o >200 ml/day and Richmond Agitation‐Sedation Scale (RASS) ≤−2, and u/o >200 ml/day and RASS ≥−1. The 3‐day mortality rates were 80.3%, 53.3%, 39.9%, and 20.6%, respectively (accuracy = 68.3%). In addition, 79.6%, 62.9%, 47.2%, 32.8%, and 17.4% of patients with P3did scores of 4, 3, 2, 1, and 0, respectively, died ≤3 days.

Conclusion

We successfully developed diagnostic models for death ≤3 days. These may further help clinicians predict impending death and help patients/families prepare for their final days.

A Prognostic Index for Predicting Survival of Patients Undergoing Radiation Therapy for Spine Metastasis Using Recursive Partitioning Analysis

Background: Physicians' estimate of life expectancy in patients with spine metastasis frequently impacts treatment decisions regarding surgery, radiation techniques, dose, and fractionation. Objective: We aimed to identify predictors of survival and generate a stratification schema that could guide clinical decision making. Materials and Methods: We identified 269 patients who have undergone surgery and/or radiation for spine metastasis from 2002 to 2013 at an academic medical institution in the United States. A univariate survival analysis was carried out using the Kaplan-Meier method. Differences in survival by histology were assessed using the log-rank test. Multivariate analysis was performed using the Cox proportional hazards model, then using the same variables, recursive partitioning analysis (RPA) was conducted to determine risk groups associated with survival. Results: The median overall survival was 4.76 months. Twenty percent, 40%, and 57% of patients died within one, three, and six months of radiation treatment, respectively. RPA analysis resulted in three classes; class I included patients with Karnofsky Performance Status (KPS) ≥80. Class II included patients with KPS <80 and radioresistant or favorable histologies. Class III included all other histologies. Median survival in months was 11.4, 6.3, and 2.0, respectively. Conclusion: We developed a stratification schema predictive of survival in patients with spine metastasis. This RPA classification should be validated in independent patient populations from several institutions and may ultimately identify patients who are good candidates for more complex treatment regimens, such as stereotactic body radiotherapy.

Identification of lenvatinib prognostic index via recursive partitioning analysis in advanced hepatocellular carcinoma

BACKGROUND

After the advent of new treatment options for advanced hepatocellular carcinoma (HCC), the identification of prognostic factors is crucial for the selection of the most appropriate therapy for each patient.

PATIENTS AND METHODS

With the aim to fill this gap, we applied recursive partitioning analysis (RPA) to a cohort of 404 patients treated with lenvatinib.

RESULTS

The application of RPA resulted in a classification based on five variables that originated a new prognostic score, the lenvatinib prognostic index (LEP) index, identifying three groups: low risk [patients with prognostic nutritional index (PNI) >43.3 and previous trans-arterial chemoembolization (TACE)]; medium risk [patients with PNI >43.3 but without previous TACE and patients with PNI <43.3, albumin-bilirubin (ALBI) grade 1 and Barcelona Clinic Liver Cancer stage B (BCLC-B)]; high risk [patients with PNI <43.3 and ALBI grade 2 and patients with PNI <43.3, albumin-bilirubin (ALBI) grade 1 and Barcelona Clinic Liver Cancer stage C (BCLC-C)]. Median overall survival was 29.8 months [95% confidence interval (CI) 22.8-29.8 months] in low risk patients (n = 128), 17.0 months (95% CI 15.0-24.0 months) in medium risk (n = 162) and 8.9 months (95% CI 8.0-10.7 months) in high risk (n = 114); low risk hazard ratio (HR) 1 (reference group), medium risk HR 1.95 (95% CI 1.38-2.74), high risk HR 4.84 (95% CI 3.16-7.43); P < 0.0001. The LEP index was validated in a cohort of 127 Italian patients treated with lenvatinib. While the same classification did not show a prognostic value in a cohort of 311 patients treated with sorafenib, we also show a possible predictive role in favor of lenvatinib in the low risk group.

CONCLUSIONS

LEP index is a promising, easy-to-use tool that may be used to stratify patients undergoing systemic treatment of advanced HCC.

Risk factors for lymph node metastasis in rectal neuroendocrine tumors: A recursive partitioning analysis based on multicenter data

BACKGROUND

The well-differentiated rectal neuroendocrine tumors (RNETs) can also have lymph node metastasis (LNM). Large multicenter data were reviewed to explore the risk factors for LNM in RNETs. Further, we developed a model to predict the risk of LNM in RNETs.

METHODS

In total, 223 patients with RNETs from the Fujian Medical University Union Hospital, the First Affiliated Hospital of Fujian Medical University, and the First Affiliated Hospital of Xiamen University were retrospectively enrolled. Logistic regression analysis was performed to study the factors affecting LNM, and recursive partitioning analysis (RPA) was performed to stratify the risk of LNM.

RESULTS

Among the 223 patients diagnosed with RNETs, the incidence of LNM was 10.8%. Univariate and multivariate regression analyses revealed that tumor size, World Health Organization (WHO) grade, and depth of tumor invasion were independent risk factors for LNM (p < 0.05). The area under the curve was 0.948 (95% confidence interval: 0.890-1.000). Furthermore, the incidence of LNM in patients divided into low- and high-risk groups according to RPA was 1.1% and 56.4%, respectively.

CONCLUSION

Compared with tumor size, the depth of tumor invasion and WHO grade are more important factors in predicting LNM. Then, we developed a model based on RPA to predict the risk of LNM in RNETs and identify patients who are suitable for local resection.

Development of a prediction model for the risk of recurrent laryngeal nerve lymph node metastasis in thoracolaparoscopic esophagectomy with cervical anastomosis

Background

There are no effective preoperative diagnostic measures to predict the probability of left and right recurrent laryngeal nerve (RLN) lymph node (LN) metastasis using preoperative clinical data in patients undergoing thoracolaparoscopic esophagectomy with cervical anastomosis.

Methods

We retrospectively reviewed the clinical data of 1,660 consecutive patients with thoracic esophageal cancer who underwent esophagectomy with cervical anastomosis at the Department of Thoracic Surgery at the First Affiliated Hospital of Zhengzhou University between January 2015 and December 2020.

Results

A total of 299 and 343 patients who underwent left (Cohort 1) and right (Cohort 2) RLN LN dissection were included in the final analyses. The analyses were conducted within each cohort. Among the 299 patients in Cohort 1, left RLN LN involvement was found in 41 patients (13.7%). A multivariable analysis showed that age, tumor location, and short axis were significantly associated with RLN LN metastasis (all P<0.05). Among the 343 patients in Cohort 2, right RLN LN involvement was found in 65 patients (19.0%). A multivariable analysis showed that computed tomography (CT) appearance, tumor location, long axis, and short axis were significantly associated with RLN LN metastasis (all P<0.05). Based on the results of the multivariable analyses, we constructed nomograms that could estimate the probability of RLN LN metastasis. Finally, we stratified the 2 cohorts into risk subgroups using a recursive partitioning analysis (RPA). The risk of left and right RLN LN metastasis was found to be 9.3% and 7.5%, 27.3% and 21.4%, and 52.4% and 47.3% for the low-risk, intermediate-risk, and high-risk groups, respectively.

Conclusions

Our nomograms and RPAs appear to be suitable for the risk stratification of left and right RLN LN metastasis in patients undergoing thoracolaparoscopic esophagectomy with cervical anastomosis. This tool could be used to help clinicians to select more effective locoregional treatments, such as surgical protocols and radiation area selection.

Indications of neoadjuvant chemotherapy for locally advanced Gastric Cancer patients based on pre-treatment clinicalpathological and laboratory parameters

Objective: There are controversial indications for neoadjuvant chemotherapy (NAT) in the treatment of locally advanced gastric cancer (LAGC). Here, we aimed to identify indications for NAT based on pre-treatment clinicopathological and laboratory parameters.

Methods: This study included a retrospective cohort of 1083 LAGC patients who had underwent radical D2 gastrectomy in the Cancer Hospital of China Medical University between 2012 and 2016. After propensity score matching, 756 patients were recruited and were separated into NAT (n=378) or primary surgery (PS) (n=378) groups. Cox regression identified pre-treatment risk factors for overall survival (OS). A nomogram was established to predict OS and calculate scores for risk factors. Recursive partitioning analysis (RPA) determined cut off values, where the entire patient cohort was divided into low and high risk groups.

Results: Seven risk factors that were significantly related to OS were incorporated in the nomogram. These risk factors included age, tumor size, tumor site, carbohydrate antigen 199 (CA199), carcino-embryonic antigen (CEA), clinical T stage (cT) and clinical N stage (cN). The model contained a C-index of 0.637. The calibration curve revealed anticipated values that were reflective of actual values. The decision curve revealed an achievement of optimal clinical impact when threshold possibility was 0-54%. Next, the cohort was split into low (≤ 252 points) or high (> 252 points) risk groups based on the 5-year OS projected by RPA. The PS group showed a worse OS compared to the NAT group for high-risk patients (P =0.004). There was no significant difference when comparing OS between the PS and NAT groups for low-risk patients (P =0.407).

Conclusions: A feasible, quantifiable and practical prognostic tool was generated to screen for potential survival benefits for patients receiving NAT. Surgeons can use this model to identify optimal treatment regimens for individualized treatment strategies during the diagnosis of LAGC patients. For these patients, NAT is suggested for high-risk patients.

Risk-Stratification of Children Presenting to Ambulatory Paediatrics with First-Onset Seizures: Should We Order an Urgent CT Brain?

INTRODUCTION

A computed tomography (CT) brain scan is an often-utilised emergency department imaging modality to detect emergent intra-cranial pathology in a child with a first seizure. Identifying children at low risk of having a clinically significant intra-cranial abnormality could prevent unnecessary radiation exposure and contrast/sedation-related risks.

OBJECTIVES

To identify clinical variables which could predict clinically significant CT brain abnormalities and use recursive partitioning analysis to define a low-risk group of children in whom emergent CT brain can be deferred.

METHODS

Retrospective cross-sectional review of 468 children who underwent emergent CT brain after presenting to a low- and middle-income paediatric emergency department following first seizure.

RESULTS

In total 133/468 (28.4%) of CT brain scans had clinically significant abnormalities. Failure to return to neurological baseline and focal neurological deficit persisting >36 h had statistical significance in a multiple regression analysis. Recursive partitioning analysis, applied to a subgroup without suspected tuberculous meningitis (n = 414), classified 153 children aged between 6 months and 5 years, who had a normal neurological baseline, had returned to baseline post-seizure, and were not in status epilepticus, as non-clinically significant scans and 98% were correctly classified.

CONCLUSION

Our study re-inforces the American Academy of Neurology recommendation that children with persistent post-ictal abnormal neurological status and/or post-ictal focal deficit be prioritised for emergent CT brain. Having excluded children with suspected tuberculous meningitis, the remaining subgroup aged 6 months to 5 years presenting with a non-status first seizure, normal neurological baseline and return to baseline post-seizure, are at very low risk of having a clinically significant CT brain abnormality.

A competing-risks nomogram and recursive partitioning analysis for cause-specific mortality in patients with esophageal neuroendocrine carcinoma

The objective of this study is to estimate the probability of cause-specific mortality using a competing-risks nomogram and recursive partitioning analysis in a large population-based cohort of patients with esophageal neuroendocrine carcinoma. The surveillance, epidemiology and end results database was used to identify 162 patients diagnosed with esophageal neuroendocrine carcinoma from 1998 to 2014. We estimated a cumulative incidence function for cause-specific mortality. A nomogram was constructed by using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with a decision curve analysis to assess its clinical utility. Finally, we performed risk stratification using a recursive partitioning analysis to divide patients with esophageal neuroendocrine carcinoma into clinically useful prognostic groups. Tumor location, distant metastasis, surgery, radiotherapy, and chemotherapy were significantly associated with cause-specific mortality. The calibration plots demonstrated good concordance between the predicted and actual outcomes. The discrimination performance of a Fine-Gray model was evaluated by using the c-index, which was 0.723 for cause-specific mortality. The decision curve analysis ranged from 0.268 to 0.968 for the threshold probability at which the risk model provided net clinical benefits relative to hypothetical all-screening and no-screening scenarios. The risk groups stratified by a recursive partitioning analysis allowed significant distinction between cumulative incidence curves. We determined the probability of cause-specific mortality in patients with esophageal neuroendocrine carcinoma and developed a nomogram and recursive partitioning analysis stratification system based on a competing-risks model. The nomogram and recursive partitioning analysis appear to be suitable for risk stratification of cause-specific mortality in patients with esophageal neuroendocrine carcinoma and will help clinicians to identify patients at increased risk of cause-specific mortality to guide treatment and surveillance decisions.

Selection and Validation of Induction Chemotherapy Beneficiaries Among Patients With T3N0, T3N1, T4N0 Nasopharyngeal Carcinoma Using Epstein-Barr Virus DNA: A Joint Analysis of Real-World and Clinical Trial Data

Background and Purpose: Evidence for induction chemotherapy plus concurrent chemoradiotherapy (IC+CCRT) in nasopharyngeal carcinoma (NPC) was derived from landmark clinical trials excluding the T3N0, T3N1, T4N0 subgroups. This study used Epstein-Barr virus (EBV) DNA to select IC beneficiaries from the three subgroups.

Materials and Methods: Significant predictors of overall survival (OS) were identified using multivariate Cox analyses. Risk stratification was generated using recursive partitioning analysis (RPA). IC+CCRT was compared with CCRT in each risk stratification and in different subgroups. Individual-level data from a clinical trial (NCT01245959) was used for validation.

Results: Gender and EBV DNA were included in RPA-generated risk stratification, categorizing patients into low-risk (EBV DNA <2,000 copies/mL; female and EBV DNA ≥2,000 copies/mL) and high-risk groups (male and EBV DNA ≥2,000 copies/mL). The OS superiority of IC+CCRT over CCRT was only observed in the high-risk group (HR = 0.64, 95% CI = 0.43–0.97; P = 0.032). Subgroup analysis indicated the OS benefit was exclusively from the docetaxel–cisplatin−5-fluorouracil regimen (HR = 0.41, 95% CI = 0.22–0.78; P = 0.005). The status of the T3N1 subgroup as an IC beneficiary is more explicit than the T3N0 and T4N0 subgroups. IC+CCRT showed improved OS in the validation cohort combining high-risk cases of real-world data with clinical trial data (HR = 0.62, 95% CI = 0.42–0.94; P = 0.023).

Conclusion: Patients with high-risk T3N1 NPC is the definite target population for receiving IC+CCRT in real-world practice. T3N0 and T4N0 subgroups need further investigations in future IC-related studies.

Development and validation of a new staging system for node-negative gastric cancer based on recursive partitioning analysis: An international multi-institutional study

BACKGROUND

Whether the tumor-node-metastasis (TNM) staging system is appropriate for patients with node-negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC.

METHODS

Node-negative GC patients who underwent radical resection at Fujian Medical University Union Hospital (n = 862) and Sun Yat-sen University Cancer Center (n = 311) with at least 5 years of follow-up were selected as the training set. RPA was used to develop a modified staging system. Patients from the Surveillance, Epidemiology, and End Results database (n = 1415) were selected as the validation set.

RESULTS

The 5-year overall survival (OS) rates of patients with 8th AJCC-TNM stage IA-IIIA in the training set were IA 95.2%, IB 87.1%, IIA 78.3%, IIB 75.8%, and IIIA 72.6%. Multivariate analysis (MVA) showed that larger tumor size, elder age, and deeper depth of invasion were independent predictors for OS in patients with node-negative GC (all P < 0.05). Patients were reclassified into RPA I, RPA II, RPA III, and RPA IV stages based on RPA; the 5-year OS rates were 96.1%, 87.2%, 81.0%, and 64.3%, respectively, with significant difference (P < 0.05). Two-step MVA showed that the RPA staging system was an independent predictor of OS (P < 0.05). Compared with the 8th AJCC-TNM staging system, the RPA staging system had a smaller AIC value (2544.9 vs 2576.2), higher χ2 score (104.2 vs 69.6) and higher Harrell's C-index (0.697 vs 0.669, P = 0.007). The similar results were found in the validation set.

CONCLUSIONS

A new prognostic predictive system based on RPA was successfully developed and validated, which may be suggested for staging node-negative GC in future.

Adaptive hypofractionated gamma knife radiosurgery in the acute management of brainstem metastases

Background:

Intrinsic brainstem metastases are life-threatening neoplasms requiring rapid, effective intervention. Microsurgery is considered not feasible in most cases and systemic treatment seldom provides a successful outcome. In this context, radiation therapy remains the best option but adverse radiation effects (ARE) remain a major concern. A dose-adaptive gamma knife procedure coined as Rapid Rescue Radiosurgery (3R) offers the possibility to treat these lesions whilst reducing the risk of ARE evolvement. We report the results of 3R applied to a group of patients with brainstem metastases.

Methods:

Eight patients with nine brainstem metastases, having undergone three separate, dose-adapted gamma knife radiosurgery (GKRS) procedures over 7 days, were retrospectively analyzed in terms of tumor volume reduction, local control rates, and ARE-development under the period of treatment and at least 6 months after treatment completion.

Results:

Mean peripheral doses at GKRS 1, GKRS 2, and GKRS 3 were 7.4, 7.7, and 8.2 Gy (range 6–9 Gy) set at the 35–50% isodose lines. Mean tumor volume reduction between GKRS 1 and GKRS 3 was −15% and −56% at first follow-up. Four patients developed radiologic signs of ARE but remained clinically asymptomatic. One patient developed a local recurrence at 34 months. Mean survival from GKRS 1 was 13 months. Two patients were still alive at the time of paper submission (10 and 23 months from GKRS 1).

Conclusions:

In this study, 3R proved effective in terms of tumor volume reduction, rescue/preservation of neurological function, and limited ARE evolvement.

Recursive Partitioning Analysis of Fractional Low-Frequency Fluctuations in Narcolepsy With Cataplexy

Objective: To identify narcolepsy related regional brain activity alterations compared with matched healthy controls. To determine whether these changes can be used to distinguish narcolepsy from healthy controls by recursive partitioning analysis (RPA) and receiver operating characteristic (ROC) curve analysis.

Method: Fifty-one narcolepsy with cataplexy patients (26 adults and 25 juveniles) and sixty matched heathy controls (30 adults and 30 juveniles) were recruited. All subjects underwent a resting-state functional magnetic resonance imaging scan. Fractional low-frequency fluctuations (fALFF) was used to investigate narcolepsy induced regional brain activity alterations among adult and juveniles, respectively. Recursive partitioning analysis and Receiver operating curve analysis was used to seek the ability of fALFF values within brain regions in distinguishing narcolepsy from healthy controls.

Results: Compared with healthy controls, both adult and juvenile narcolepsy had lower fALFF values in bilateral medial superior frontal gyrus, bilateral inferior parietal lobule and supra-marginal gyrus. Compared with healthy controls, both adult and juvenile narcolepsy had higher fALFF values in bilateral sensorimotor cortex and middle temporal gyrus. Also juvenile narcolepsy had higher fALFF in right putamen and right thalamus compared with healthy controls. Based on RPA and ROC curve analysis, in adult participants, fALFF differences in right medial superior frontal gyrus can discriminate narcolepsy from healthy controls with high degree of sensitivity (100%) and specificity (88.9%). In juvenile participants, fALFF differences in left superior frontal gyrus can discriminate narcolepsy from healthy controls with moderate degree of sensitivity (57.1%) and specificity (88.9%).

Conclusion: Compared with healthy controls, both the adult and juvenile narcolepsy showed overlap brain regions in fALFF differences after case-control comparison. Furthermore, we propose that fALFF value can be a helpful imaging biomarker in distinguishing narcolepsy from healthy controls among both adults and juveniles.

The concept of rapid rescue radiosurgery in the acute management of critically located brain metastases: A retrospective short-term outcome analysis

Background:

Adaptive hypofractionated gamma knife radiosurgery has been used to treat brain metastases in the eloquent regions while limiting the risk of adverse radiation effect (ARE). Ablative responses might be achieved within days to weeks with the goal to preserve the neurological function. The application of this treatment modality in selected acute/subacute settings has been termed Rapid Rescue Radiosurgery (RRR) in our department. We report the expeditious effects of RRR during treatment and 4 weeks after treatment completion.

Methods:

In all, 34 patients with 40 brain metastases, each treated over a period of 7 days in three separate gamma knife radiosurgery sessions (GKRS 1-3) between November 2013 and August 2017, were retrospectively analyzed in terms of tumor volume reduction, salvage of organs at risk (OAR), and radiation induced toxicity under the period of treatment (GKRS 1-3 = one week) and at first follow-up magnetic resonance imaging (MRI) (4 weeks after GKRS 3).

Results:

Mean tumor volume at GKRS 1 was 12.8 cm3. Mean peripheral doses at GKRS 1, GKRS 2, and GKRS 3 were 7.7 Gy, 8.1 Gy, and 8.4 Gy (range: 6.0-9.5 Gy) at the 35% to 50% isodose lines. In the surviving group at first follow-up (n = 28), mean tumor volume reduction was − 10% at GKRS 3 (1 week) and − 48% four weeks after GKRS 3. There was no further clinical deterioration between GKRS 3 and first follow-up in 21 patients. Six patients died prior to first follow-up due to extracranial disease. No ARE was noticed/reported.

Conclusions:

In this study, RRR proved effective in terms of rapid tumor volume reduction, debulking, and preservation/rescue of neurological function.

Proposed modifications and incorporation of plasma Epstein-Barr virus DNA improve the TNM staging system for Epstein-Barr virus-related nasopharyngeal carcinoma

BACKGROUND

The prognosis of patients who have Epstein-Barr virus (EBV)-related nasopharyngeal carcinoma (NPC) in which the tumor tissues harbor EBV have a better prognosis than those without EBV-related NPC. Therefore, the eighth edition of the TNM staging system could be modified for EBV-related NPC by incorporating the measurement of plasma EBV DNA.

METHODS

In total, 979 patients with NPC who received intensity-modulated radiotherapy (IMRT) were retrospectively reviewed. Recursive partitioning analysis was conducted based on tumor (T) classification, lymph node (N) classification, and EBV DNA measurement to derive objectively the proposed stage groupings. The validity of the proposed stage groupings was confirmed in a prospective cohort of 550 consecutive patients who also received with IMRT.

RESULTS

The pretreatment plasma EBV DNA level was identified as a significant, negative prognostic factor for progression-free survival and overall survival in univariate analysis (all P < .001) and multivariate analysis (all P < .05). Recursive partitioning analysis of the primary cohort to incorporate EBV DNA generated the following proposed stage groupings: stage RI (T1N0), RIIA (T2-T3N0 or T1-T3N1, EBV DNA ≤2000 copies/mL), stage RIIB (T2-T3N0 or T1-T3N1, EBV DNA >2000 copies/mL; T1-T3N2, EBV DNA ≤2000 copies/mL), stage RIII (T1-T3N2, EBV DNA >2000 copies/mL; T4N0-N2), and stage RIVA (any T and N3). In the validation cohort, the 5-year progression-free survival rate was 100%, 87.9%, 76.7%, 68.7%, and 50.4% for proposed stage RI, RIIA, RIIB, RIII, and RIV NPC, respectively (P < .001). Compared with the eighth edition TNM stage groupings, the proposed stage groupings incorporating EBV DNA provided better hazard consistency, hazard discrimination, outcome prediction, and sample size balance.

CONCLUSIONS

The proposed stage groupings have better prognostic performance than the eighth edition of the TNM staging system. EBV DNA titers should be included in the TNM staging system to assess patients who have EBV-related NPC.

Combining Washout and Noncontrast Data From Adrenal Protocol CT: Improving Diagnostic Performance

RATIONALE AND OBJECTIVES

To determine if combination of washout and noncontrast data from delayed adrenal computed tomography (CT) improves diagnostic performance, and demonstration of an optimizing analytical framework.

MATERIALS AND METHODS

This retrospective study consisted of 97 adrenal lesions, in 96 patients, with pathologically proven adrenal lesions (75 benign; 22 malignant), who had undergone noncontrast, portal- and approximate 15-minute delayed-phase CT. Lesion CT attenuations (Hounsfield units [HU]) during each phase, and "absolute" and "relative" percent enhancement washouts (APEW and RPEW) were assessed. The optimum combination of sequential parameters and thresholds was determined by recursive partitioning analysis; resultant diagnostic performance was compared to commonly applied single-parameter criteria for malignancy (noncontrast > 10 HU, APEW < 60%, RPEW < 40%).

RESULTS

The above single-parameter criteria yielded sensitivities, specificities, and accuracies for malignancy of 100.0%, 41.3%, and 54.6%; 97.9%, 61.3%, and 69.1%; and 96.6%, 74.7%, and 78.4%, respectively. Recursive partitioning analysis identified noncontrast ≥24.75 HU, with subsequent APEW ≤63.49%, as the optimum sequential parameter-threshold combination, which yielded increased sensitivity, specificity, and accuracy of 100.0%, 85.3%, and 90.7%, respectively. Discrimination using the combined sequential classifier yielded statistically significant improvements in accuracy when compared to the above conventional single-parameter criteria (all P ≤ .039).

CONCLUSION

Sequential application of noncontrast and washout criteria from delayed contrast-enhanced adrenal CT can improve diagnostic performance beyond that of commonly applied single-parameter criteria. Validation of the sequential ordering and refinement of the specific threshold values warrant further study.

A prognostic nomogram for overall survival after neoadjuvant radiotherapy or chemoradiotherapy in thoracic esophageal squamous cell carcinoma: a retrospective analysis

BACKGROUND

Currently, the AJCC staging system or pathological complete response (pCR) are considered not sufficiently accurate to evaluate the survival of patients with esophageal squamous cell carcinoma after neoadjuvant radiotherapy or chemoradiotherapy. This study aimed to establish a nomogram and a recursive partitioning analysis (RPA) model to estimate prognosis and to provide advice for subsequent treatments.

METHODS

We analyzed retrospectively 407 patients that were diagnosed with thoracic esophageal squamous cell carcinoma (TESCC) and received neoadjuvant radiotherapy or chemoradiotherapy. Hazard ratios and 95% confidence intervals of categorical clinicopathological characteristics with overall survival (OS) were calculated using the Cox proportional hazard model. The nomogram and RPA model were then established and total scores according to each variable were calculated and stratified to predict OS.

RESULTS

Patients were followed-up over a median 49.9 months. AJCC did not perform well in distinguishing OS among each stage except for IIB and IIIA. Patients were divided into 4 groups according to the total scores based on nomogram (low risk: ≤180; intermediate risk: 180-270; high risk: 270-340; very high risk: >340). The 5-year OS was 57.3%, 40.7%, 18.3%, 6.1% respectively (p<0.05). RPA model also divide the patients into 4 groups, though group2 and group3 were not statistically significant (p=0.574).

CONCLUSION

The nomogram is a good evaluation model for estimating the prognosis of patients with TESCC after neoadjuvant radiotherapy or chemoradiotherapy compared with the AJCC and RPA. The results of this study also suggested that the high-risk subgroups need further treatments.

Stratification according to recursive partitioning analysis predicts outcome in newly diagnosed glioblastomas

Glioblastoma accounts for more than half of diffuse gliomas. The prognosis of patients with glioblastoma remains poor despite comprehensive and intensive treatments. Furthermore, the clinical significance of molecular parameters and routinely available clinical variables for the prognosis prediction of glioblastomas remains limited. The authors describe a novel model may help in prognosis prediction and clinical management of glioblastoma patients. We performed a recursive partitioning analysis to generate three independent prognostic classes of 103 glioblastomas patients from TCGA dataset. Class I (MGMT promoter methylated, age <58), class II (MGMT promoter methylation, age ≥58; MGMT promoter unmethylation, age <54, KPS ≥70; MGMT promoter unmethylation, age >59, KPS ≥70), class III (MGMT promoter unmethylation, age 54-58, KPS ≥70; MGMT promoter unmethylation, KPS <70). Age, KPS and MGMT promoter methylation were the most significant prognostic factors for overall survival. The results were validated in CGGA dataset.

This was the first study to combine various molecular parameters and clinical factors into recursive partitioning analysis to predict the prognosis of patients with glioblastomas. We included MGMT promoter methylation in our study, which could give better suggestion to patients for their chemotherapy. This clinical study will serve as the backbone for the future incorporation of molecular prognostic markers currently in development. Thus, our recursive partitioning analysis model for glioblastomas may aid in clinical prognosis evaluation.

Adjuvant treatment may benefit patients with high-risk upper rectal cancer: A nomogram and recursive partitioning analysis of 547 patients

Purpose

The role of adjuvant chemoradiotherapy (ACRT) or adjuvant chemotherapy (ACT) in treating patients with locally advanced upper rectal cancer (URC) after total mesorectal excision (TME) surgery remains unclear. We developed a clinical nomogram and a recursive partitioning analysis (RPA)-based risk stratification system for predicting 5-year cancer-specific survival (CSS) to determine whether these individuals require ACRT or ACT.

Materials and Methods

This retrospective analysis included 547 patients with primary URC. A nomogram was developed based on the Cox regression model. The performance of the model was assessed by concordance index (C-index) and calibration curve in internal validation with bootstrapping. RPA stratified patients into risk groups based on their tumor characteristics.

Results

Five independent prognostic factors (age, preoperative increased carcinoembryonic antigen and carcinoma antigen 19-9, positive lymph node [PLN] number, tumor deposit [TD], pathological T classification) were identified and entered into the predictive nomogram. The bootstrap-corrected C-index was 0.757. RPA stratification of the three prognostic groups showed obviously different prognosis. Only the high-risk group (patients with PLN ≤ 6 and TD, or PLN > 6) benefited from ACRT plus ACT when compared with surgery followed by ACRT or ACT, and surgery alone (5-year CSS: 70.8% vs. 57.8% vs. 15.6%, P < 0.001).

Conclusions

Our nomogram predicts 5-year CSS after TME surgery for locally advanced rectal cancer and RPA-based stratification indicates that ACRT plus ACT post-surgery may be an important treatment plan with potentially significant survival advantages in high-risk URC. This may help to select candidates of adjuvant treatment in prospective studies.

Nomogram and recursive partitioning analysis to predict overall survival in patients with stage IIB-III thoracic esophageal squamous cell carcinoma after esophagectomy

We have developed statistical models for predicting survival in patients with stage IIB-III thoracic esophageal squamous cell carcinoma (ESCC) and assessing the efficacy of adjuvant treatment. From a retrospective review of 3,636 patients, we created a database of 1,004 patients with stage IIB-III thoracic ESCC who underwent esophagectomy with or without postoperative radiation. Using a multivariate Cox regression model, we assessed the prognostic impact of clinical and histological factors on overall survival (OS). Logistic analysis was performed to identify factors to include in a recursive partitioning analysis (RPA) to predict 5-year OS. The nomogram was evaluated internally based on the concordance index (C-index) and a calibration plot. The median survival time in the training dataset was 30.9 months, and the 5-year survival rate was 33.9%. T stage, differentiated grade, adjuvant treatment, tumor location, lymph node metastatic ratio (LNMR), and the presence of vascular carcinomatous thrombi were statistically significant predictors of 5-year OS. The C-index of the nomogram was 0.70 (95% CI 0.67-0.73). RPA resulted in a three-class stratification: class 1, LNMR ≤ 0.15 with adjuvant treatment; class 2, LNMR ≤ 0.15 without adjuvant treatment and LNMR > 0.15 with adjuvant treatment; and class 3, LNMR > 0.15 without adjuvant treatment. The three classes were statistically significant for OS (P < 0.001). Thus, the nomogram and RPA models predicted the prognosis of stage IIB-III ESCC patients and could be used in decision-making and clinical trials.

Evaluation of a prognostic scoring system based on the systemic inflammatory and nutritional status of patients with locally advanced non-small-cell lung cancer treated with chemoradiotherapy

Systemic inflammation and poor nutritional status have a negative effect on the outcomes of cancer. Here, we analyzed the effects of the pretreatment inflammatory and nutritional status on clinical outcomes of locally advanced non-small-cell lung cancer (NSCLC) patients treated with chemoradiotherapy. We retrospectively reviewed 89 patients with locally advanced NSCLC treated with chemoradiotherapy between July 2006 and June 2013. Serum C-reactive protein (CRP) was assessed as an inflammatory marker, and serum albumin, body mass index (BMI) and skeletal mass index were assessed as nutritional status markers. The relationships between these markers and overall survival (OS) were assessed. The median OS was 24.6 months [95% confidence interval (CI): 19.4-39.3 months]. During follow-up, 58 patients (65%) had disease recurrence and 52 patients (58%) died. In multivariate Cox hazard analysis, CRP levels and BMI approached but did not achieve a significant association with OS (P = 0.062 and 0.094, respectively). Recursive partitioning analysis identified three prognostic groups based on hazard similarity (CRP-BMI scores): 0 = CRP < 0.3 mg/dl, 1 = CRP ≥ 0.3 mg/dl and BMI ≥ 18.5 kg/m2, and 2 = CRP ≥ 0.3 mg/dl and BMI < 18.5 kg/m2. The CRP-BMI score was significantly associated with OS (P = 0.023). Patients with scores of 0, 1 and 2 had median OS of 39.3, 24.5 and 14.5 months, respectively, and the scores also predicted the probability of receiving salvage treatment after recurrence. The CRP-BMI score is thus a simple and useful prognostic marker of clinical outcome for patients with locally advanced NSCLC treated with chemoradiotherapy.

Establishment of an integrated model incorporating standardised uptake value and N-classification for predicting metastasis in nasopharyngeal carcinoma

Background

Previous studies reported a correlation between the maximum standardised uptake value (SUV_max) obtained by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) and distant metastasis in nasopharyngeal carcinoma (NPC). However, an integrated model incorporating SUV_max and anatomic staging for stratifying metastasis risk has not been reported.

Results

The median SUV_max for primary tumour (SUV-T) and cervical lymph nodes (SUV-N) was 13.6 (range, 2.2 to 39.3) and 8.4 (range, 2.6 to 40.9), respectively. SUV-T (HR, 3.396; 95% CI, 1.451-7.947; P = 0.005), SUV-N (HR, 2.688; 95%CI, 1.250-5.781; P = 0.011) and N-classification (HR, 2.570; 95%CI, 1.422-4.579; P = 0.001) were identified as independent predictors for DMFS from multivariate analysis. Three valid risk groups were derived by RPA: low risk (N0-1 + SUV-T <10.45), medium risk (N0-1 + SUV-T >10.45) and high risk (N2-3). The three risk groups contained 100 (22.3%), 226 (50.3%), and 123 (27.4%) patients, respectively, with corresponding 3-year DMFS rates of 99.0%, 91.5%, and 77.5% (P <0.001). Moreover, multivariate analysis confirmed the RPA-based prognostic grouping as the only significant prognostic indicator for DMFS (HR, 3.090; 95%CI, 1.975-4.835; P <0.001).

Methods

Data from 449 patients with with histologically-confirmed, stage I-IVB NPC treated with radiotherapy or chemoradiotherapy were retrospectively analysed. A prognostic model for distant metastasis-free survival (DMFS) was derived by recursive partitioning analysis (RPA) combining independent predictors identified by multivariate analysis.

Conclusion

SUV-T, SUV-N and N-classification were identified as independent predictors for DMFS. An integrated RPA-based prognostic model for DMFS incorporating SUV-N and N-classification was proposed.

Intensity-modulated radiation therapy for patients with 1 to 3 brain metastases in recursive partitioning analysis class 3

The prognosis is extremely poor for patients with brain metastases in recursive partitioning analysis (RPA) class 3. It is not clear whether dose elevation for brain lesions in addition to whole-brain radiotherapy could improve survival for those patients. This study aimed to assess the efficacy and safety of dose elevation with intensity-modulated radiation therapy (IMRT) for patients with 1 to 3 brain metastases in RPA class 3.From January 2013 to December 2015, 24 patients with 1 to 3 brain metastases in RPA class 3 were included in this study. The median age was 60 (range 41-85) years and the mean graded prognostic assessment (GPA) score was 1.25 (range 0.5-2). Whole-brain radiotherapy (30 Gy) with a simultaneous integrated boost (SIB) to the brain metastases (totaling 40 Gy) was delivered in 10 fractions using IMRT technique. Survival times and overall safety were assessed. The significance of prognostic variables on survival was assessed by both univariate and multivariate analyses.All of the patients completed the planned SIB schedule. The overall response rate was 66.7%. The median survival time (MST) was 8 months for the entire group of patients. The MST was 5 months for patients with a GPA score of 0.5 to 1 (n = 11 patients) and 12 months with a GPA score of 1.5 to 2 (n = 13 patients). No acute or late toxicities greater than grade 2 were detected. Age and subsequent chemotherapy were significantly associated with MST on univariate and multivariate analyses.It is feasible to elevate radiation doses to 40 Gy using the IMRT technique in RPA class 3 patients with 1 to 3 brain metastases without serious toxicities. The preliminary results are encouraging and further studies with larger cohorts are warranted.

Adaptive hypofractionated gamma knife radiosurgery in the acute management of large thymic carcinoma brain metastases

BACKGROUND

Brain metastases often lead to serious neurological impairment and life threatening states. Their acute management remains complex, particularly in the case of rare malignancies with aggressive evolution. In large single lesions, open surgery followed by radiation to the surgical cavity is widely regarded as the best approach; yet in many cases, microsurgery is not feasible due to the lesion's critical location and/or the number of brain metastases present. We report the effects of adaptive hypofractionated gamma knife radiosurgery in the acute management of critically located thymic carcinoma metastases.

CASE DESCRIPTION

A 50-year-old male with metastatic thymic carcinoma was treated with radiosurgery for two large supratentorial brain metastases (M3 and M4) adjacent to eloquent areas and one smaller cerebellar metastasis (M2). M3 and M4 were treated with adaptive hypofractionated gamma knife radiosurgery, showing a dramatic volume reduction 4 weeks after treatment completion without radiation-induced side effects. Thirteen months later, two new small, threatening supratentorial lesions (M5-M6) were treated with the same technique. Interestingly, M2 (treated with standard single fraction) and M5-M6 developed local adverse radiation events. The patient's general and neurological status remained next to normal by the time of paper submission.

CONCLUSION

The application of adaptive hypofractionated radiosurgery in this acute setting proved effective in terms of rapid tumor ablation, with salvage of neurological functionality and limited toxicity. We have called the overall procedure rapid rescue radiosurgery (RRR). A systematic study of past and ongoing RRR-treatments is warranted and in progress.

Comparison of prognostic indices in patients who undergo melanoma brain metastasis radiosurgery

OBJECTIVE The goal of this study was to use 4 prognostic indices to compare survival times of patients who underwent Gamma Knife stereotactic radiosurgery (SRS) to treat melanoma brain metastases. METHODS The authors analyzed 422 consecutive patients (1440 brain metastases) who underwent Gamma Knife SRS. The median total brain tumor volume was 4.7 cm³ (range 0.3-69.3 cm³), and the median number of metastases was 2 (range 1-32). One hundred thirty-two patients underwent whole-brain radiation therapy. Survival times were compared using recursive partitioning analysis (RPA), the Score Index for Radiosurgery (SIR), the Basic Score for Brain Metastases (BSBM), and the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA). RESULTS The overall survival times after SRS were compared. With the RPA index, survival times were 2.6 months (Class III, n = 27), 5.5 months (Class II, n = 348), and 13.0 months (Class I, n = 47). With the DS-GPA index, survival times were 2.8 months (Scores 0-1, n = 67), 4.2 months (Scores 1.5-2.0, n = 143), 6.6 months (Scores 2.5-3.0, n = 111), and 9.4 months (Scores 3.5-4.0, n = 101). With the SIR, survival times were 3.2 months (Scores 0-3, n = 56), 5.8 months (Scores 4-7, n = 319), and 12.7 months (Scores 8-10, n = 47). With the BSBM index, survival times were 2.6 months (BSBM0, n = 47), 5.4 months (BSBM1, n = 282), 11.0 months (BSBM2, n = 86), and 8.8 months (BSBM3, n = 7). The DS-GPA index was the most balanced by case numbers in each class and provided the overall best prognostic index for overall survival. CONCLUSIONS The DS-GPA index proved most balanced and predictive of survival for patients with melanoma who underwent SRS as part of management for brain metastases. Patients whose DS-GPA score was ≥ 2.5 had predictably improved survival times after SRS.

Adaptive hypofractionated gamma knife radiosurgery for a large brainstem metastasis

Background:

To demonstrate how adaptive hypofractionated radiosurgery by gamma knife (GK) can be successfully utilized to treat a large brainstem metastasis - a novel approach to a challenging clinical situation.

Case Description:

A 42-year-old woman, diagnosed with metastatic nonsmall cell lung cancer in July 2011, initially treated with chemotherapy and tyrosine kinase inhibitors, developed multiple brain metastases March 2013, with subsequent whole brain radiotherapy, after which a magnetic resonance imaging (MRI) showed a significant volume regression of all brain metastases. A follow-up MRI in October 2013 revealed a growing brainstem lesion of 26 mm. Linear accelerator-based radiotherapy and microsurgery were judged contraindicated, why the decision was made to treat the patient with three separate radiosurgical sessions during the course of 1 week, with an 18% tumor volume reduction demonstrated after the last treatment. Follow-up MRI 2.5 months after her radiosurgical treatment showed a tumor volume reduction of 67% compared to the 1^st day of treatment. Later on, the patient developed a radiation-induced perilesional edema although without major clinical implications. An MRI at 12 months and 18-fluoro-deoxyglucose positron emission tomography of the brain at 13 months showed decreased edema with no signs of tumor recurrence. Despite disease progression during the last months of her life, the patient's condition remained overall acceptable.

Conclusion:

GK-based stereotactic adaptive hypofractionation proved to be effective to achieve tumor control while limiting local adverse reactions. This surgical modality should be considered when managing larger brain lesions in critical areas.

Recursive partitioning analysis of prognostic variables in newly diagnosed anaplastic oligodendroglial tumors

BACKGROUND

Anaplastic oligodendroglial tumors are rare, and median survival varies widely. Analysis of 1p19q deletion is performed commonly and is an important prognostic factor. However, age and other clinical variables also carry prognostic value, and it is unclear how to incorporate them into clinical decision making or to combine them for prognostication.

METHODS

We compiled a retrospective database of 1013 patients with newly diagnosed anaplastic oligodendrogliomas or oligoastrocytomas and performed a recursive partitioning analysis to generate independent prognostic classes among 587 patients with informative 1p19q status. Variables included for survival classification were age (continuous), history of prior low-grade glioma, 1p19q deletion status, histology (presence or absence of an astrocytic component), tumor lobe, tumor hemisphere, gender, extent of resection, postresection treatment, and performance status at diagnosis.

RESULTS

Recursive partitioning analysis identified 5 prognostic groups based on hazard similarity: class I (age <60 y, 1p19q codeleted), class II (age <43 y, not codeleted), class III (age 43-59 y, not codeleted, frontal lobe tumor or age ≥60 y, codeleted), class IV (age 43-59 y, not codeleted, not frontal lobe tumor or age 60-69 y, not codeleted), and class V (age ≥70 y, not codeleted). Survival differences were highly significant (P < .0001), with medians ranging from 9.3 years (95% CI: 8.4-16.0) for class I to 0.6 years (95% CI: 0.5-0.9) for class V.

CONCLUSIONS

These 5 distinct classification groups were defined using prognostic factors typically obtained during routine management of patients with anaplastic oligodendroglial tumors. Validation in a prospective clinical trial may better differentiate patients with respect to treatment outcome.

Risk groups defined by Recursive Partitioning Analysis of patients with colorectal adenocarcinoma treated with colorectal resection

BACKGROUND

To define different prognostic groups of surgical colorectal adenocarcinoma patients derived from recursive partitioning analysis (RPA).

METHODS

Ten thousand four hundred ninety four patients with colorectal adenocarcinoma underwent colorectal resection from Taiwan Cancer Database during 2003 to 2005 were included in this study. Exclusion criteria included those patients with stage IV disease or without number information of lymph nodes. For the definition of risk groups, the method of classification and regression tree was performed. Main primary outcome was 5-year cancer-specific survival.

RESULTS

We identified six prognostic factors for cancer-specific survival, resulting in seven terminal nodes. Four risk groups were defined as following: Group 1 (mild risk, 1,698 patients), Group 2 (moderate risk, 3,129 patients), Group 3 (high risk, 4,605 patients) and Group 4 (very high risk, 1,062 patients). The 5-year cancer-specific survival for Group 1, 2, 3, and 4 was 86.6%, 62.7%, 55.9%, and 36.6%, respectively (p < 0.001). Hazard ratio of death was 2.13, 5.52 and 10.56 (95% confidence interval 1.74-2.60, 4.58-6.66 and 8.66-12.9, respectively) times for Group 2, 3, and 4 as compared to Group 1. The predictive capability of these grouping was also similar in terms of overall and progression-free survival.

CONCLUSION

The use of RPA offered an alternative grouping method that could predict the survival of patients who underwent surgery for colorectal adenocarcinoma.

Recursive Partitioning Analysis of Mediastinal N2 Lymph Node Involvement with Selected Biological Markers in Operable Non-small Cell Lung Cancer: A Correlative Study

BACKGROUND

Expressions of various biomarkers in non-small cell lung cancer (NSCLC) have been linked with the prognosis and involvement of mediastinal lymph nodes.

METHODS

In this study, we utilized recursive partitioning analysis (RPA) by using P53, c-erb-B2, and P-glycoprotein (PGP) expressions evaluated by immunohistochemistry to estimate retrospectively the likelihood of the occult N2 mediastinal lymph node involvement in patients with operable NSCLC.

RESULTS

In univariate tests, immunohistochemical staining of the primary tumor for these 3 markers in 61 patients undergoing surgery revealed no direct relationship with the N2 involvement. However, RPA demonstrated in patients aged <75 and with >/=4 mediastinal lymph nodes removed that, high PGP expression frequency (>/=20%) predicted an increased likelihood of the N2 involvement (46.7%, R(2) = 0.25). Univariate nominal logistic regression analysis revealed that RPA group affiliation, and the number of mediastinal lymph nodes resected (logarithmic transformation) were associated with the metastasis to N2 lymph nodes (chi(2) = 17.59, p = 0.0005, and chi(2) = 2.40, p = 0.0654, respectively). Multivariate analysis confirmed that only RPA group affiliation predicted the N2 involvement (chi(2) = 14.63, p = 0.0022).

CONCLUSION

This study shows for the first time that PGP expression of the primary tumor may help to predict the occult N2 mediastinal lymph node involvement in NSCLC. Thus, further research is required to understand whether PGP expression may aid in the decision process for preoperative mediastinoscopy.