Nutritional status and symptom burden in advanced non-small cell lung cancer: results of the dietetic assessment and intervention in lung cancer (DAIL) trial

INTRODUCTION

European Society for Clinical Nutrition and Metabolism guidelines recommend that patients with cancer should be screened for malnutrition at diagnosis. The dietetic assessment and intervention in lung cancer study investigated the nutritional status of patients with non-small cell lung cancer (NSCLC) and the need for dietetic intervention.

METHODS

In this observational cohort pilot study, patients with stage 3b and 4 NSCLC were assessed prior to starting first line systemic anticancer therapy (SACT) with a range of measurements and questionnaires. We report the outcomes related to the Patient Generated Subjective Global Assessment tool (PG-SGA), RESULTS: 96 patients were consented between April 2017 and August 2019. The PG-SGA identified that 78% of patients required specialist nutritional advice; with 52% patients having a critical need for dietetic input and symptom management. Results were dominated by symptom scores. As a screening test, one or more symptoms or recent weight loss history had a sensitivity of 88% (95% CI 78.44% to 94.36%) and specificity of 95.24% (95% CI 76.18% to 99.88%) for need for dietetic intervention.

CONCLUSION

A large proportion of patients with NSCLC have a high symptom burden and are at risk of malnutrition prior to starting SACT and would benefit from dietetic review. It is imperative that oncologists and healthcare professionals discuss weight loss history and symptoms with lung cancer patients to correct nutritional deficiencies and resolve symptoms prior to starting treatment.

The stability of imaging biomarkers in radiomics: a framework for evaluation

This paper studies the sensitivity of a range of image texture parameters used in radiomics to: (i) the number of intensity levels, (ii) the method of quantisation to select the intensity levels and (iii) the use of an intensity threshold. 43 commonly used texture features were studied for the gross target volume outlined on the CT component of PET/CT scans of 50 patients with non-small cell lung carcinoma (NSCLC). All cases were quantised for all values between 4 and 128 intensity levels using four commonly used quantisation methods. All results were analysed with and without a threshold range of  -200 HU to 300 HU. Cases were ranked for each texture feature and for all quantisation methods with the Spearman's rank correlation coefficient determined to evaluate stability. Results showed large fluctuations in ranking, particularly for low numbers of levels, differences between quantisation methods and with the use of a threshold, with values Spearman's Rank Correlation for many parameters below 0.2. Our results demonstrated the sensitivity of radiomics features to the parameters used during analysis and highlight the risk of low reproducibility comparing studies with slightly different parameters. In terms of the lung cancer CT datasets, this study supports the use of 128 intensity levels, the same uniform quantiser applied to all scans and thresholding of the data. It also supports several of the features recommended in the literature for such studies such as skewness and kurtosis. A recommended framework is presented for curation of the data analysis process to ensure stability of results.

Textural analysis and lung function study: Predicting lung fitness for radiotherapy from a CT scan

OBJECTIVE

This study tested the hypothesis that shows advanced image analysis can differentiate fit and unfit patients for radical radiotherapy from standard radiotherapy planning imaging, when compared to formal lung function tests, FEV1 (forced expiratory volume in 1 s) and TLCO (transfer factor of carbon monoxide).

METHODS

An apical region of interest (ROI) of lung parenchyma was extracted from a standard radiotherapy planning CT scan. Software using a grey level co-occurrence matrix (GLCM) assigned an entropy score to each voxel, based on its similarity to the voxels around it.

RESULTS

Density and entropy scores were compared between a cohort of 29 fit patients (defined as FEV1 and TLCO above 50 % predicted value) and 32 unfit patients (FEV1 or TLCO below 50% predicted). Mean and median density and median entropy were significantly different between fit and unfit patients (p = 0.005, 0.0008 and 0.0418 respectively; two-sided Mann-Whitney test).

CONCLUSION

Density and entropy assessment can differentiate between fit and unfit patients for radical radiotherapy, using standard CT imaging.

ADVANCES IN KNOWLEDGE

This study shows that a novel assessment can generate further data from standard CT imaging. These data could be combined with existing studies to form a multiorgan patient fitness assessment from a single CT scan.

Prophylactic Irradiation of Tracts in Patients With Malignant Pleural Mesothelioma: An Open-Label, Multicenter, Phase III Randomized Trial

PURPOSE

Prophylactic irradiation to the chest wall after diagnostic or therapeutic procedures in patients with malignant pleural mesothelioma (MPM) has been a widespread practice across Europe, although the efficacy of this treatment is uncertain. In this study, we aimed to determine the efficacy of prophylactic radiotherapy in reducing the incidence of chest wall metastases (CWM) after a procedure in MPM.

METHODS

After undergoing a chest wall procedure, patients with MPM were randomly assigned to receive prophylactic radiotherapy (within 42 days of the procedure) or no radiotherapy. Open thoracotomies, needle biopsies, and indwelling pleural catheters were excluded. Prophylactic radiotherapy was delivered at a dose of 21 Gy in three fractions over three consecutive working days, using a single electron field adapted to maximize coverage of the tract from skin surface to pleura. The primary outcome was the incidence of CWM within 6 months from random assignment, assessed in the intention-to-treat population. Stratification factors included epithelioid histology and intention to give chemotherapy.

RESULTS

Between July 30, 2012, and December 12, 2015, 375 patients were recruited from 54 centers and randomly assigned to receive prophylactic radiotherapy (n = 186) or no prophylactic radiotherapy (n = 189). Participants were well matched at baseline. No significant difference was seen in the incidence of CWM at 6 months between the prophylactic radiotherapy and no radiotherapy groups (no. [%]: 6 [3.2] v 10 [5.3], respectively; odds ratio, 0.60; 95% CI, 0.17 to 1.86; P = .44). Skin toxicity was the most common radiotherapy-related adverse event in the prophylactic radiotherapy group, with 96 patients (51.6%) receiving grade 1; 19 (10.2%), grade 2; and 1 (0.5%) grade 3 radiation dermatitis (Common Terminology Criteria for Adverse Events, version 4.0).

CONCLUSION

There is no role for the routine use of prophylactic irradiation to chest wall procedure sites in patients with MPM.

Corrigendum: Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution

This corrects the article DOI: 10.1038/nature22364.

Clinical applications of textural analysis in non-small cell lung cancer

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed "radiomics" and includes semantic and agnostic approaches. Textural analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue subtypes of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarize the current published data and understand the potential future role of TA in managing lung cancer.

Tracking the Evolution of Non-Small-Cell Lung Cancer

BACKGROUND

Among patients with non-small-cell lung cancer (NSCLC), data on intratumor heterogeneity and cancer genome evolution have been limited to small retrospective cohorts. We wanted to prospectively investigate intratumor heterogeneity in relation to clinical outcome and to determine the clonal nature of driver events and evolutionary processes in early-stage NSCLC.

METHODS

In this prospective cohort study, we performed multiregion whole-exome sequencing on 100 early-stage NSCLC tumors that had been resected before systemic therapy. We sequenced and analyzed 327 tumor regions to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between intratumor heterogeneity and recurrence-free survival.

RESULTS

We observed widespread intratumor heterogeneity for both somatic copy-number alterations and mutations. Driver mutations in EGFR, MET, BRAF, and TP53 were almost always clonal. However, heterogeneous driver alterations that occurred later in evolution were found in more than 75% of the tumors and were common in PIK3CA and NF1 and in genes that are involved in chromatin modification and DNA damage response and repair. Genome doubling and ongoing dynamic chromosomal instability were associated with intratumor heterogeneity and resulted in parallel evolution of driver somatic copy-number alterations, including amplifications in CDK4, FOXA1, and BCL11A. Elevated copy-number heterogeneity was associated with an increased risk of recurrence or death (hazard ratio, 4.9; P=4.4×10-4), which remained significant in multivariate analysis.

CONCLUSIONS

Intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, a finding that supports the potential value of chromosome instability as a prognostic predictor. (Funded by Cancer Research UK and others; TRACERx ClinicalTrials.gov number, NCT01888601 .).

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies.

Mathematical modelling of tumour volume dynamics in response to stereotactic ablative radiotherapy for non-small cell lung cancer

This paper reports a modelling study of tumour volume dynamics in response to stereotactic ablative radiotherapy (SABR). The main objective was to develop a model that is adequate to describe tumour volume change measured during SABR, and at the same time is not excessively complex as lacking support from clinical data. To this end, various modelling options were explored, and a rigorous statistical method, the Akaike information criterion, was used to help determine a trade-off between model accuracy and complexity. The models were calibrated to the data from 11 non-small cell lung cancer patients treated with SABR. The results showed that it is feasible to model the tumour volume dynamics during SABR, opening up the potential for using such models in a clinical environment in the future.