Neutrophil–Lymphocyte and Platelet–Lymphocyte Ratios as Prognostic Factors after Stereotactic Radiation Therapy for Early-Stage Non–Small-Cell Lung Cancer

IntroductionThe hematologic indices of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are correlated with clinical outcomes after stereotactic radiation.MethodsWe retrospectively evaluated the pretreatment NLR and PLR in patients treated with stereotactic radiation for early stage non–small-cell lung cancer at our institution. A total of 149 patients treated for non–small-cell lung cancer were identified, and 59 had stage I disease with neutrophil, platelet, and lymphocyte levels within a 3-month period before treatment. Receiver operating characteristic (ROC) analysis was performed to examine cutoff values for survival and nonlocal failure followed by Kaplan–Meier analysis for survival.ResultsWith a median follow-up of 17 months, 28 deaths were observed, and the median overall survival for all patients was 43 months. Based on the ROC analysis, NLR and PLR cutoff values for further survival analysis were determined based on the ROC analysis to be 2.98 and 146. The median overall survival was not reached for patients with low NLR or PLR but the survival was 23 months for patients with high NLR or PLR. There was no correlation between NLR and nonlocal failure, but on multivariate analysis PLR was found to be associated with freedom from nonlocal failure. Nonlocal failure rates were 11% for patients with PLR less than 250 and 58% for PLR greater than 250 (p < 0.001).ConclusionThe pretreatment NLR and PLR represented significant prognostic indicators of survival in patients treated for early-stage non–small-cell lung carcinoma with stereotactic radiation. The PLR may be used as a prognostic indicator for nonlocal failure after stereotactic radiation for early-stage lung cancer

Defining oligometastatic disease from a radiation oncology perspective : an ESTRO-ASTRO consensus document

Background: Recognizing the rapidly increasing interest and evidence in using metastasis-directed radiotherapy (MDRT) for oligometastatic disease (OMD), ESTRO and ASTRO convened a committee to establish consensus regarding definitions of OMD and define gaps in current evidence. Methods: A systematic literature review focused on curative intent MDRT was performed in Medline, Embase and Cochrane. Subsequent consensus opinion, using a Delphi process, highlighted the current state of evidence and the limitations in the available literature. Results: Available evidence regarding the use of MDRT for OMD mostly derives from retrospective, single-centre series, with significant heterogeneity in patient inclusion criteria, definition of OMD, and outcomes reported. Consensus was reached that OMD is largely independent of primary tumour, metastatic location and the presence or length of a disease-free interval, supporting both synchronous and metachronous OMD. In the absence of clinical data supporting a maximum number of metastases and organs to define OMD, and of validated molecular biomarkers, consensus supported the ability to deliver safe and clinically meaningful radiotherapy with curative intent to all metastatic sites as a minimum requirement for defining OMD in the context of radiotherapy. Systemic therapy induced OMD was identified as a distinct state of OMD. High-resolution imaging to assess and confirm OMD is crucial, including brain imaging when indicated. Minimum common endpoints such as progression-free and overall survival, local control, toxicity and quality-of-life should be reported; uncommon endpoints as deferral of systemic therapy and cost were endorsed. Conclusion: While significant heterogeneity exists in the current OMD definitions in the literature, consensus was reached on multiple key questions. Based on available data, OMD can to date be defined as 1–5 metastatic lesions, a controlled primary tumor being optional, but where all metastatic sites must be safely treatable. Consistent definitions and reporting are warranted and encouraged in ongoing trials and reports generating further evidence to optimize patient benefits

Randomized Phase II Study Comparing Prophylactic Cranial Irradiation Alone to Prophylactic Cranial Irradiation and Consolidative Extracranial Irradiation for Extensive-Disease Small Cell Lung Cancer (ED SCLC): NRG Oncology RTOG 0937

Introduction—RTOG-0937 is a randomized phase-II trial evaluating 1-year OS with PCI or PCI plus consolidative radiation therapy (cRT) to intra-thoracic disease and extracranial metastases for ED-SCLC. Methods—Patients with 1–4 extracranial metastases were eligible after CR or PR to chemotherapy. Randomization was to PCI or PCI+cRT to the thorax and metastases. Original stratification included PR vs CR after chemotherapy and 1 vs 2–4 metastases; age \u3c 65 vs ≥ 65 was added after an observed imbalance. PCI was 25GY/10 fractions. cRT was 45GY/15 fractions. To detect an OS improvement from 30% to 45% with a 34% hazard reduction (HR=0·66) under a 0.1 type-1 error (1-sided) and 80% power, 154 patients were required. Results—Ninety-seven patients were randomized between March, 2010 and February, 2015. Eleven patients were ineligible (nine PCI, two PCI+cRT), leaving 42 randomized to PCI and 44 to PCI+cRT. At planned interim analysis the study crossed the futility boundary for OS and was closed prior to meeting accrual target. Median follow-up was 9 months. One-year OS was not different between the groups: 60.1% [95% CI: 41.2–74.7%] for PCI and 50.8% [95% CI:34.0–65.3%] for PCI+cRT (p=0.21). Three and 12-month rates of progression were 53.3% and 79.6% for PCI, and 14.5% and 75% for PCI+cRT. Time to progression favored PCI+cRT, HR=0.53 (95% CI: 0.32–0.87, p=0.01). One-patient in each arm had Grade-4 therapy related toxicity and one had Grade-5 therapy related pneumonitis with PCI+cRT. Conclusions—OS exceeded predictions for both arms. Consolidative RT delayed progression but did not improve 1-year OS

Toward more precise radiotherapy treatment of lung tumors

A computational framework for modeling the respiratory motion of lung tumors provides a 4D parametric representation that tracks, analyzes, and models movement to provide more accurate guidance in the planning and delivery of lung tumor radiotherapy. © 2012 IEEE

Driver Missense Mutation Identification Using Feature Selection and Model Fusion

Driver mutations propel oncogenesis and occur much less frequently than passenger mutations. The need for automatic and accurate identification of driver mutations has increased dramatically with the exponential growth of mutation data. Current computational solutions to identify driver mutations rely on sequence homology. Here we construct a machine learning–based framework that does not rely on sequence homology or domain knowledge to predict driver missense mutations. A windowing approach to represent the local environment of the sequence around the mutation point as a mutation sample is applied, followed by extraction of three sequence-level features from each sample. After selecting the most significant features, the support vector machine and multimodal fusion strategies are employed to give final predictions. The proposed framework achieves relatively high performance and outperforms current state-of-the-art algorithms. The ease of deploying the proposed framework and the relatively accurate performance make this solution applicable to large-scale mutation data analyses