Lung cancer is a common disease leading to 18% of all cancer deaths worldwide. Prognosis of lung cancer depends on various factors like disease stage, socioeconomic factors, body composition factors such as sarcopenia have been shown to be associated with poor prognosis and survival. Sarcopenia is defined as decline in muscle strength, muscle quantity/quality (skeletal muscle mass) and physical performance. Diagnosis of sarcopenia is confirmed by demonstrating reduced skeletal muscle mass while physical performance can be used to assess severity of sarcopenia. In past 5 years there are some studies indicating an association between treatment of lung cancer and decline in parameters of sarcopenia. Although remarkable improvements in medical treatments for non-small cell lung cancer (NSCLC) based on chemotherapy, targeted therapy and immunotherapy have been made, advanced lung cancer patients still have low five-year survival rate at 10-20 percent. Notably with a high prevalence of 43%, sarcopenia is shown to be a significant predictor of worsening overall survival and poor prognosis in NSCLC patients.

Cancer patients have expedited decline in skeletal muscle mass as compared to normal age-related decline in patients without cancer. Majority of older studies on NSCLC patients show that there is decrease in skeletal muscle mass during chemotherapy. Data on changes in skeletal muscles in NSCLC patients receiving targeted therapy and immunotherapy are limited, however studies suggest that patients experience decline in skeletal muscle mass while receiving these therapies as well. During treatment, in addition to decline in skeletal muscle mass, non-small cell lung cancer patients also exhibit decline in other parameters of sarcopenia i.e., muscle strength and physical performance as well. The impact of decline in parameters of sarcopenia leads to functional impairment with poor response to treatment, increased drug toxicities and poor quality of life. The value of measuring sequential decline in parameters of sarcopenia is not clearly understood. It is believed that interventions to treat sarcopenia can evolve if we can understand effects of different cancer therapies on sarcopenia. Early screening and treatment of sarcopenia in these patients may help to prevent functional impairment and improve overall survival.

Although there are other causes of sarcopenia in cancer patients such as impaired nutritional intake, low physical activity, causes relating to cancer therapies are not well established. There still remains a wide knowledge gap in understanding decline in different parameters of sarcopenia while patients are on different types of lung cancer treatment. Therefore, we aim to study a prospective cohort to evaluate differences in rate of decline in skeletal muscle mass and physical performance in advanced NSCLC patients receiving chemotherapy and targeted therapy/immunotherapy. The skeletal muscle mass and physical performance will be evaluated using computed tomography (CT) and short physical performance battery (SPPB) respectively. There is lack of validated cut-off values for CT-defined skeletal muscle mass in Thai population. Therefore, in Thai population, we aim to validate the cutoff values set by Japanese Society of Hepatology(JSH) based on recommendation of Asian Working Group for Sarcopenia (AWGS). As latest consensus on sarcopenia highlights importance of physical performance, if there exist an association between CT-defined skeletal muscle mass and physical performance, the former can be used in predicting physical functioning of patients. Therefore, we intend to determine baseline association between CT-defined skeletal muscle mass and physical performance as well. As far as we know there are no previous studies done to evaluate the differences in decline in skeletal muscle mass in patients who are unable to complete their first line chemotherapy and receive other line of chemotherapy (chemotherapy agents which are not considered first line), therefore we intent to study these differences too. Finally, this study also includes an evaluation of overall response rate of chemotherapy in patients with low CT-defined skeletal muscle mass.

This study is based in Songklanagarind Hospital and enrollment of participants will be as per our inclusion criteria which includes advanced lung cancer patients who are more than 18 years old treated with either chemotherapy, targeted therapy or immunotherapy. The sample size required for the study was estimated using simulation in Stata, with an estimated total N=240. According to treatment recommended by primary chest physician, participants will be divided into groups of chemotherapy (CMT) and targeted/immunotherapy (TKI/IO). Measurement of variables will take place in four different time period. Baseline characteristics will be measured before starting the treatment. The outcome variables our study i.e., computed tomography (CT)-defined skeletal muscle mass, short physical performance battery (physical performance) and health related quality of life using Thai Version of EQ-5D-5L Health Questionnaire (EQ-5D-5L) will be measured before starting treatment (T1), after 3rd, 6th and 9th months (T2, T3 and T4) of treatment. Additionally, after 3rd cycle of treatment "response evaluation criteria in solid tumors" (RECIST v1.1) will be recorded to evaluate response rate of chemotherapy. For patients who are unable to tolerate first line chemotherapy, they will be recruited for our 1st secondary objective and patients in this group will be evaluated only for CT-defined skeletal muscle mass in subsequent time period. At the end of our study, we will have three groups of patients i.e., patients receiving first line chemotherapy (CMT) patients on first line targeted/immunotherapy (TKI/IO) and patients on other line chemotherapy (OCMT).

Measuring skeletal muscle area (SMA) at L3 vertebral level using computed tomography scan is used to estimate total body skeletal muscle mass (SMM). Height adjusted SMA, also called skeletal muscle index (SMI) can be calculated by dividing SMA by patient's height square. As our study is based on Thai population, cut-off for diagnosis of CT-defined sarcopenia will be taken as L3 lumbar vertebra (L3SMI) \<42cm2/m2 for men and \<38 cm2/m2 for women. Short physical performance battery (SPPB) test will be used to evaluate physical performance. SPPB consists of set of three tests including balance test, gait test and 5 times chair stand test. Patients are asked to stand side-by-side, semi-tandem and tandem to measure balance. And then patients are asked to walk 4 meters to assess gait speed. Chair stand test is performed by asking the patient to fold their arms and stand up from seated position for five times. Points from 0 to 12 will be given according to time required to perform above tests. Health related quality of life will be measured using the Thai Version of EQ-5D-5L Health Questionnaire. This is validated tool for use in Thailand which has a self-completed questionnaire for adults consisting of 5 dimensions of mobility, self-care, usual activities, pain/discomfort and anxiety/depression The baseline characteristics will be presented with n (%) and mean (SD) or median (IQI) as appropriate. Chi-square test (or Fisher Exact test), Student t-test (or Kruskal-Wallis test) will be calculated to evaluate the differences of baseline data between CMT and TKI/IO groups. The baseline correlation between SPPB and SMI will be presented with scatter plot and LOWESS line. The change of SMI after 6th cycles of treatments and the differences of the change between CMT and TKI/IO groups will be calculated using Student t-test or Kruskal-Wallis test. Multivariable linear regression will be used to adjust the imbalance of baseline characteristics between these two-groups. Decline in SMI for CMT and OCMT will be calculated using same analysis. The rate of decline in SMI (and SPPB score) will be calculated using multilevel-linear regression (Mixed linear regression) and will be shown in two-way graph. The response rate to chemotherapy will be analyzed using logistic regression. The p-value of less the 0.05 will be considered statistically significant. The analysis and graphically figures will be shown using Stata/MP 17.0, StataCorp, 4905 Lakeway Dr, College Station, TX 77845, USA.