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.

Dietetic assessment and intervention in lung cancer.

PURPOSE OF REVIEW: Systemic therapy for lung cancer is increasing in intensity and duration. European nutrition guidelines suggest screening for weight loss and malnutrition, however acknowledges there is a lack of evidence. We discuss current data round this issue and identify opportunities for further research. RECENT FINDINGS: International guidelines now exist to aid the definition of weight loss in cancer, including cachexia, sarcopenia and malnutrition. These allow consistent definition of overlapping, but distinct clinical syndromes. Nutritional status can be assessed in a range of ways including questionnaires, functional assessments, blood markers, physical activity, weight and BMI. Weight loss is commonly associated with a proinflammatory state. Future treatment is likely to be a combination of dietetic support and pharmacological treatment of cachexia. SUMMARY: There is a paucity of data on dietetic intervention. It is potentially quick, inexpensive and patient specific, using a holistic approach to aid patients who are malnourished or at risk of malnutrition. Lung cancer-related weight loss is common, further strategies are needed to effectively assess and intervene. Dietetic intervention has the potential to improve patients' quality of life and outcomes.

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.

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.

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.

Factors influencing the robustness of P-value measurements in CT texture prognosis studies.

Several studies have recently reported on the value of CT texture analysis in predicting survival, although the topic remains controversial, with further validation needed in order to consolidate the evidence base. The aim of this study was to investigate the effect of varying the input parameters in the Kaplan-Meier analysis, to determine whether the resulting P-value can be considered to be a robust indicator of the parameter's prognostic potential. A retrospective analysis of the CT-based normalised entropy of 51 patients with lung cancer was performed and overall survival data for these patients were collected. A normalised entropy cut-off was chosen to split the patient cohort into two groups and log-rank testing was performed to assess the survival difference of the two groups. This was repeated for varying normalised entropy cut-offs and varying follow-up periods. Our findings were also compared with previously published results to assess robustness of this parameter in a multi-centre patient cohort. The P-value was found to be highly sensitive to the choice of cut-off value, with small changes in cut-off producing substantial changes in P. The P-value was also sensitive to follow-up period, with particularly noisy results at short follow-up periods. Using matched conditions to previously published results, a P-value of 0.162 was obtained. Survival analysis results can be highly sensitive to the choice in texture cut-off value in dichotomising patients, which should be taken into account when performing such studies to avoid reporting false positive results. Short follow-up periods also produce unstable results and should therefore be avoided to ensure the results produced are reproducible. Previously published findings that indicated the prognostic value of normalised entropy were not replicated here, but further studies with larger patient numbers would be required to determine the cause of the different outcomes.

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.