Kamyar Mansori1,2, Fatemeh Khosravi Shadmani3, Shiva Mansouri Hanis4, Salman Khazaei5. 1. Social Development & Health Promotion Research Center, Gonabad University of Medical Sciences, Gonabad, Iran. 2. Department of Epidemiology, School of Public Health, Iran University of Medical Science, Tehran, Iran. 3. Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. 4. Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5. Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
To the editor:We were interested to read the paper by Hye-Sang Park with entitled “Role of physical activity in mortality prediction in elderly hospice patients “which was published in Journal of Exercise Rehabilitation in April 2017. The aim of this study was to investigate the mortality predictors and indicators of life extension among elderly patients in a hospice service center. The results revealed that the time of death negatively correlated with activities of daily living (ADL) score (r=−0.273, P=0.006). However, the Korean-Mini Mental State Examination & Global Deterioration Scale, and the values of blood component such as albumin, gamma-glutamic transpeptidase, blood ureanitrogen, and creatinine were not correlated with the time of death. Consequently, the ADL score might be an important predictor of mortality and life extension in elderly patients. Finally, this study concludes that in order to improve ADL score, physical exercise and overall fitness may be potential nonpharmacologic methods useful in preventing mortality in elderly people (Park et al., 2017). However, regardless of the results of the study that are interesting, some methodological issues should be considered relating to this cross-sectional study.First, for prediction studies, we need data from two different cohorts or at least from one cohort divided into two to first to develop a prediction model and subsequently validate it. Misleading results are generally the main outcome of research that fails to validate its prediction models (Rothman et al., 2008; Sani et al., 2016; Sabour, 2017). And also, without the temporality assumption (the dependent variable must occur after the independent variable) there is no way of determining whether a factor is a risk factor, is predictive/causal, or is a consequence of the outcome (Hanis et al., 2017; Mansori et al., 2017). Therefore, longitudinal studies are essential for developing assumptions to be used in clinical prediction models, whereas in this study, a cross-sectional study was used to identify the independent predictors for mortality prediction in elderly hospice patients. Therefore, it is essential to interpret the results of this study in light of the above explanation.