A survival analysis using physique-adjusted tumor size of non-small cell lung cancer
- 140 Downloads
Differences in individual body sizes have not been well considered when analyzing the survival of patients with non-small cell lung cancer (NSCLC). We hypothesized that physique-adjusted tumor size is superior to actual tumor size in predicting the prognosis.
Eight hundred and forty-two patients who underwent R0 resection of NSCLC between 2005 and 2012 were retrospectively reviewed, and overall survival (OS) was evaluated. The physique-adjusted tumor size was defined as: x-adjusted tumor size = tumor size × mean value of x/individual value of x [x = height, weight, body surface area (BSA), or body mass index (BMI)]. Tumor size category was defined as ≤2, 2–3, 3–5, 5–7, and >7 cm. The separation index (SEP), which is the weighted mean of the absolute value of estimated regression coefficients over the subgroups with respect to a reference group, was used to measure the separation of subgroups.
The mean values of height, weight, BSA, and BMI were 160.7 cm, 57.6 kg, 1.59 m2, and 22.2 kg/m2, respectively. The 5-year survival rates ranged from 88−59% in the non-adjusted tumor size model (SEP 1.937), from 90−57% in the height-adjusted model (SEP 2.236), from 91−52% in the weight-adjusted model (SEP 2.146), from 90−56% in the BSA-adjusted model (SEP 2.077), and from 91−51% in the BMI-adjusted model (SEP 2.169).
The physique-adjusted tumor size can separate the survival better than the actual tumor size.
KeywordsLung cancer Body size Height Weight BMI Survival
Compliance with ethical standards
Conflict of interest
The authors have declared that no conflict of interest exists.
- 7.Sobin L, Gospodarowicz M, Wittekind C (eds) (2009) TNM Classification of malignant tumors, 7th edn. Wiley, HobokenGoogle Scholar
- 8.Travis WD, Brambilla E, Burke AP et al (2015) WHO classification of tumours of the lung, pleura, thymus and heart, 4th edn. IARC Press, LyonGoogle Scholar
- 16.Altman DG (1990) Practical statistics for medical research. Chapman and Hall/CRC Texts in Statistical Science, LondonGoogle Scholar