Six-Month Survivorship Prediction in Spinal Metastatic Patients by Oncologists Shows Reliable Prognostication.

STUDY DESIGN: A retrospective analysis of oncologist-provided prognoses vs actual survival outcomes of patients referred with Metastatic spinal cord compression (MSCC) to a supra-regional multidisciplinary team (MDT). OBJECTIVES: Prognostic scoring systems, such as the revised Tokuhashi, are commonly used to help guide the treatment of MSCC. However, scoring systems do not accommodate for the improved outcomes of contemporary cancer therapy. Oncologist-provided prognoses play an important role in real world rapid decision making. There is a paucity of evidence assessing the accuracy of the oncologist-provided prognosis. We conducted a retrospective study to evaluate this. METHODS: Data was captured between January 2015 and December 2018. Patients were split into 2 groups: Group 1 (prognosis estimated <6 months) and Group 2 (prognosis estimated >6 months). Median overall survival (mOS) and hazard ratio for death (HR) was assessed. Receiver operating characteristic (ROC) analysis was performed to assess the accuracy of the oncologist's prognosis. RESULTS: 829 patients were included. mOS in Group 1 was 5.8 months (95% CI 4.2-7.4 m), and in Group 2 mOS was not reached. Log rank test gave a Chi2 of 131 (P < .001). Cox regression analysis revealed a HR of .30 (P < .001). Area under the ROC curve was 78%. CONCLUSIONS: Oncologist-provided prognosis is accurate in this cohort of unselected, consecutive MSCC patients. It reduced reliance on scoring systems that can become outdated. Given the rapid progress in cancer treatment, the oncologist's prognostic prediction is integral in efficient and effective MSCC management to help rapidly determine surgical candidacy.

The evolution of lung cancer and impact of subclonal selection in TRACERx.

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource.

A new prognostic model for predicting 30-day mortality in acute oncology patients.

INTRODUCTION: Acute oncology services (AOS) provide rapid review and expedited pathways for referral to specialist care for cancer patients. Blood tests may support AOS in providing estimates of prognosis. We aimed to develop and validate a prognostic model of 30-day mortality based on routine blood markers to inform an AOS decision to actively treat or palliate patients. METHODS AND MATERIALS: Using clinical data from 752 AOS referrals, multivariable logistic regression analysis was conducted to develop a 30-day mortality prognostic model. Internal validation and then internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. RESULTS: Urea, alkaline phosphatase, albumin and neutrophils were the strongest predictors of outcome. The model separated patients into distinct prognostic groups from the cross-validation (C Statistic: 0.70; 95% CI: 0.64-0.76). Admission year was included as a predictor in the model to improve the model calibration. CONCLUSION: The developed prediction model was able to classify patients into distinct prognostic risk groups, which is clinically useful for delivering an evidence-based AOS. Collation of data from other AOS centers would allow for the development of a more generalizable prognostic model.

Cytoreductive nephrectomy in the current treatment algorithm.

The two recent prospective randomized trials CARMENA and SURTIME have changed the therapy paradigm of metastatic renal cell carcinoma. The CARMENA trial was conducted to investigate whether cytoreductive nephrectomy (CN) is required in the targeted therapy area, whereas SURTIME studied whether deferred CN in combination with sunitinib can be used to identify patients with inherent targeted therapy resistance. In the current review, we provide a comprehensive discussion of two randomized studies and the current evidence with up-do-date algorithms for treating primary metastatic clear-cell renal cell carcinoma in the era of targeted therapy and immune-checkpoint inhibition.