|Year : 2017 | Volume
| Issue : 2 | Page : 478-480
Novel use of bioelectric impedence technique to detect alterations in body composition in advanced small cell lung cancer
A Mohan, R Poulose, A Ansari, K Madan, V Hadda, GC Khilnani, R Guleria
Department of Pulmonary Medicine and Sleep Disorders, All India Institute of Medical Sciences, New Delhi, India
|Date of Web Publication||21-Feb-2018|
Dr. A Mohan
Department of Pulmonary Medicine and Sleep Disorders, All India Institute of Medical Sciences, New Delhi
Source of Support: None, Conflict of Interest: None
BACKGROUND: Malnutrition is frequent in lung cancer and is measured using various tools, including the novel bioelectric impedance technique for measuring body composition. However, the validation of this technique for assessing body composition in advanced small cell lung cancer (SCLC) is untested. METHODS: Forty-one treatment naïve patients (all males) and an equal number of age- and sex-matched controls were evaluated by anthropometric measurements of skinfold thicknesses and body composition parameters such as body fat%, fat mass, fat-free mass (FFM), and total body water (TBW). RESULTS: The mean (SD) age of the patient group was 55.7 (7.5) years, median pack-years was 20 (range, 0-80), and mean (SD) duration of symptoms was 152.6 (153.7) days. Median Karnofsky Performance Scale was 70 (range, 50–90). Majority of our patients (68.3%) were Stage IV followed by Stage III (31.7%). The percentage of patients with low, normal, and high body mass index (BMI) was 31.7%, 61%, and 7.3%, respectively. All components of body composition, i.e., body fat%, FFM, and TBW were significantly lower in patients compared to controls. However, the body composition in patients and controls with normal BMI was similar. The phenomenon of sarcopenia as a cause of cancer cachexia may explain these findings, whereas the combination of loss of body fat and lean body mass may lead to weight loss and reduced BMI. CONCLUSION: Our results indicate that body composition is markedly altered in Indian patients with advanced SCLC. The impact of these parameters on clinically relevant outcomes needs further evaluation.
Keywords: Bioelectric impedance, body composition, fat mass, small cell lung cancer
|How to cite this article:|
Mohan A, Poulose R, Ansari A, Madan K, Hadda V, Khilnani G C, Guleria R. Novel use of bioelectric impedence technique to detect alterations in body composition in advanced small cell lung cancer. Indian J Cancer 2017;54:478-80
|How to cite this URL:|
Mohan A, Poulose R, Ansari A, Madan K, Hadda V, Khilnani G C, Guleria R. Novel use of bioelectric impedence technique to detect alterations in body composition in advanced small cell lung cancer. Indian J Cancer [serial online] 2017 [cited 2022 Nov 29];54:478-80. Available from: https://www.indianjcancer.com/text.asp?2017/54/2/478/225808
| » Introduction|| |
Lung cancer is associated with significant malnutrition which has important implications on quality of life and prognosis. Small cell lung cancer (SCLC) is a particularly aggressive variant, characterized by early, widespread metastases, and extremely low survival rates. In recent years, determination of body composition has been shown to be novel and non-invasive surrogate indicator of malnutrition in cancer patients and a reliable predictor of survival and length of hospitalization.,
Body composition is measured using the technique of bioelectric impedance analysis (BIA), which is based on the electrical properties of body tissues. At a frequency of 50 kHz, small currents can pass through both the intra- and extra-cellular fluid, in varying proportions depending on the tissue characteristics. Single frequency BIA at 50 kHz can be used for the estimation of individual components of body composition such as body fat percentage, fat mass, fat-free mass (FFM), and total body water (TBW) using predictive equations. Although the significance of malnutrition per se in lung cancer is well known, scant information is available regarding the use of this novel technique of body composition analysis in lung cancer, especially small cell carcinoma. The few previous studies have shown conflicting results and were conducted on small patient groups that included other cancers apart from the lung. SCLC, in particular, has been relatively less studied probably due to its lower prevalence. Baracos et al. demonstrated that 61% of males and 31% of females in his non-SCLC group had an underlying sarcopenia, even when only a quarter of the patients presented with symptoms of weight loss. It is possible that body composition of Indian patients may differ from other populations based on ethnicity or geographical location. We hypothesized that the disease process in the relatively aggressive SCLC morphology is likely to significantly alter the body composition in Indian patients. The aim of our study was therefore to compare the body composition of treatment naïve SCLC patients with that of age- and gender-matched healthy controls.
| » Methods|| |
A retrospective chart review was conducted of all newly diagnosed patients with SCLC visiting the All India Institute of Medical Sciences, New Delhi over a period of three years from 2012 to 2015. Patient demographics, clinical history, and smoking history were obtained. Based on their smoking status, patients were grouped as current smokers, former smokers (those who had quit smoking for at least the last 6 months), or nonsmokers (lifetime pack-years <10). Performance status was determined using the Karnofsky Performance Scale (KPS) which consists of an 11-point scale ranging from 0 (dead) to 100 (asymptomatic with normal activities). Age- and sex-matched healthy controls were recruited prospectively after excluding significant medical conditions based on history and physical examination.
Body composition analysis
Basal metabolic rate, TBW, fat mass, and FFM were calculated by bioelectric impedance method using TANITA total body fat 300 body composition analyzer (Tanita Corp., IL, USA). The platform of the analyzer is composed of pressure contact stainless steel footpad electrodes. Herein, after entering the age, sex, and height of the individual into the analyzer, they were asked to stand on the platform barefoot, and a 500 μA alternating current at 50 kHz was passed through the electrodes. A printed report of the above-mentioned parameters was obtained within 10 s.
Descriptive statistics were used to determine the frequency of symptoms and KPS. Mean and standard deviation (SD) was calculated for continuous variables. Comparison between two groups was done using Student's t- test. P < 0.05 was considered as statistically significant. All the statistical tests done in this study were two-tailed and STATA 11.0 version for Windows (STATA Corporation, College Station Road, Houston, Texas, USA) was used for data analysis.
| » Results|| |
A total of 41 patients (all males; the solitary female patient was excluded) and 41 age-matched controls (all males) were studied. The mean SD age of the patient group was 55.7 (7.5) years, median pack-years was 20 (range, 0–80) and mean SD duration of symptoms was 152.6 (153.7) days. The most common symptoms were cough (70.7%), chest pain (65.9%), fatigue (63.4%), loss of weight (60.9%), loss of appetite (58.5%), and shortness of breath (53.7%). Median KPS was 70 (range, 50–90). Majority of our patients (68.3%) were Stage IV followed by Stage III (31.7%). The proportion of patients with low, normal and high body mass index (BMI) was 31.7%, 61%, and 7.3%, respectively. [Table 1] shows the anthropometric parameters and six minute walk distance of the study group. [Table 2] depicts the comparative analysis of body composition between all patients and controls. All components of body composition were significantly lower in patients compared to controls. However, when these parameters were compared only between patients and controls with normal BMI, no difference was observed [Table 3].
|Table 1: Six-minute walk distance and anthropometric parameters of small cell lung cancer patients (n=41)|
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|Table 2: Comparison of body composition parameters between patients and control subjects|
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|Table 3: Comparison between patients and controls with normal body mass index|
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| » Discussion|| |
Our results indicate that body composition is significantly altered in treatment-naive SCLC patients. Although the majority of our patients had normal weight, their body fat% was significantly lower compared to healthy controls. However, when patients with normal BMI were compared with controls having similar BMI, the body composition was similar across the two groups.
Altered lipid metabolism, including reduced lipogenesis and increased lipid mobilization may lead to the loss of body fat., One of the defining features of cancer cachexia is sarcopenia, and increased degradation of protein has been demonstrated in skeletal muscles of cachectic patients., This combination of loss of body fat and loss of lean body mass could lead to weight loss in lung cancer.
Literature regarding body composition in cancer is scarce, and previous studies have yielded conflicting results. In a study of 311 patients with solid tumors, Fouladiun et al. demonstrated a disproportionally higher loss of body fat compared to the loss of lean body mass. Maturo et al. studied 11 patients with prostate cancer and demonstrated that lean body mass, but not fat mass was significantly lower in patients compared to age- and BMI-matched controls. Moley et al. in a study of 104 patients with upper gastrointestinal malignancies demonstrated a proportional loss of both fat and body cell mass. Heymsfield andMcManus. demonstrated similar results in a longitudinal study in 9 cancer patients. Our results are contrasting, wherein patients and controls with normal BMI had similar body composition. The reasons may depend on the different type of cancer and the fact that all our subjects were treatment naïve.
We compared patients with matched controls to negate the effects of age and sex on body composition. Age has been demonstrated to have an effect on body composition. Bemben et al., demonstrated that increased age is associated with increased body fat and declining fat-free mass. In addition, females tend to have greater adiposity compared to males.
Body composition has also been linked to outcome parameters. Body fat had been demonstrated to be one of the predictors of survival in solid tumors, whereas lean body mass lacked any predictive value. Lower fat-free mass has been proposed as an independent risk factor for malnutrition and increased the duration of hospital stay. The lower body fat also has an impact on the cytotoxicity of antineoplastic drugs by its effect on the volume of distribution of antineoplastic drugs, as demonstrated by Prado et al., who showed that lean body mass was a significant predictor of cytotoxicity in 5-Fluorouracil chemotherapy.
There were some obvious limitations in this study. The study design was retrospective and lacked dietary history. Follow-up information of patients was not available to track further changes in body composition. However, considering our relatively larger sample size of patients compared to previous reports and age- and sex-matched control group, we had a good statistical power to evaluate body composition of SCLC. To the best of our knowledge, this is the first study to look at body composition parameters in a larger group comprising solely SCLC patients using the novel bioimpedance technique. This information may be useful in designing appropriate nutritional interventions to attempt to improve clinical outcomes. More extensive studies, with a larger sample size and including both male and female patients are required to evaluate the temporal change in body composition in SCLC and its utility as a prognostic or monitoring parameter.
| » Conclusion|| |
Indian patients with advanced SCLC have markedly altered body composition and malnutrition when measured using a novel bioelectric impedance technique. The prognostic implication of these observations needs further exploration for elucidating the clinical utility of this technique.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]
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