1.A comparison of breast cancer survival among young, middle-aged, and elderly patients in southern Iran using Cox and empirical Bayesian additive hazard models.
Samane NEMATOLAHI ; Seyyed Mohammad Taghi AYATOLLAHI
Epidemiology and Health 2017;39(1):e2017043-
OBJECTIVES: A survival analysis of breast cancer patients in southern Iran according to age has yet to be conducted. This study aimed to quantify the factors contributing to a poor prognosis, using Cox and empirical Bayesian additive hazard (EBAH) models, among young (20-39 years), middle-aged (40-64 years), and elderly (≥ 65 years) women. METHODS: Data from 1,574 breast cancer patients diagnosed from 2002 to 2012 in the cancer registry of Fars Province (southern Iran) were stratified into 3 age groups. The Kaplan-Meier method was used to estimate the overall survival rates. Cox and EBAH models were applied to each age category, and the Akaike information criterion was used to assess the goodness-of-fit of the 2 hazard models. RESULTS: As of December 2012, 212 women (13.5%) in our study population had died, of whom 43 were young (15.3%), 134 middle-aged (11.8%), and 35 elderly (22.3%). The 5-year survival probability by age category was 0.83 (standard error [SE], 0.03), 0.88 (SE, 0.01), and 0.75 (SE, 0.04), respectively. CONCLUSIONS: The Nottingham Prognostic Index was the most effective prognostic factor. The model based on Bayesian methodology performed better with various sample sizes than the Cox model, which is the most widely used method of survival analysis.
Aged*
;
Breast Neoplasms*
;
Breast*
;
Female
;
Humans
;
Iran*
;
Methods
;
Prognosis
;
Proportional Hazards Models*
;
Sample Size
;
Survival Rate
2.A comparison of breast cancer survival among young, middle-aged, and elderly patients in southern Iran using Cox and empirical Bayesian additive hazard models
Samane NEMATOLAHI ; Seyyed Mohammad Taghi AYATOLLAHI
Epidemiology and Health 2017;39(1):2017043-
OBJECTIVES: A survival analysis of breast cancer patients in southern Iran according to age has yet to be conducted. This study aimed to quantify the factors contributing to a poor prognosis, using Cox and empirical Bayesian additive hazard (EBAH) models, among young (20-39 years), middle-aged (40-64 years), and elderly (≥ 65 years) women.METHODS: Data from 1,574 breast cancer patients diagnosed from 2002 to 2012 in the cancer registry of Fars Province (southern Iran) were stratified into 3 age groups. The Kaplan-Meier method was used to estimate the overall survival rates. Cox and EBAH models were applied to each age category, and the Akaike information criterion was used to assess the goodness-of-fit of the 2 hazard models.RESULTS: As of December 2012, 212 women (13.5%) in our study population had died, of whom 43 were young (15.3%), 134 middle-aged (11.8%), and 35 elderly (22.3%). The 5-year survival probability by age category was 0.83 (standard error [SE], 0.03), 0.88 (SE, 0.01), and 0.75 (SE, 0.04), respectively.CONCLUSIONS: The Nottingham Prognostic Index was the most effective prognostic factor. The model based on Bayesian methodology performed better with various sample sizes than the Cox model, which is the most widely used method of survival analysis.
Aged
;
Breast Neoplasms
;
Breast
;
Female
;
Humans
;
Iran
;
Methods
;
Prognosis
;
Proportional Hazards Models
;
Sample Size
;
Survival Rate
3.Longitudinal standards for growth velocity of infants from birth to 4 years born in West Azerbaijan Province of northwest Iran.
Parvin GHAEMMAGHAMI ; Seyyed Mohammad Taghi AYATOLLAHI ; Vahid ALINEJAD ; Elham HAEM
Epidemiology and Health 2015;37(1):e2015029-
OBJECTIVES: Growth velocity is an important factor to monitor for appropriate child growth. This study presents the growth velocity of infants based on length, weight, and head circumference. METHODS: The subjects of this study were 308 neonates (160 boys and 148 girls) born in West Azerbaijan Province of northwestern Iran who were followed from birth for 4 years. The weights and lengths of the subjects were recorded at birth, 1, 2, 4, 6, and 9 months, and 1, 1.5, 2, 3, and 4 years of age, while the head circumferences were measured just up to 1.5 years of age. In this study, the Lambda-Mu-Sigma (LMS) method using LMS Chartmaker Pro (Institute of Child Health, London, UK) was utilized to obtain growth velocity percentiles. RESULTS: After obtaining growth velocity charts for weight, length, and head circumference (5th, 50th, and 95th percentiles), the researchers could deduce that there was a sharp decrease in the velocity growth charts from birth to 2 years of age but these charts remained relatively stable up to 4 years for both sexes. Growth velocities for the length and weight of boys in the present sample are slightly but not significantly greater than those in girls through the first months of infancy and there was no significant difference between girls and boys up to 4 years. CONCLUSIONS: This paper provided the first local growth velocity standards of length, weight, and head circumference for infants by analyzing longitudinal measurements produced for West Azerbaijan Province, which should be updated periodically. It seems that there has been a significant difference between the growth velocity of infants in northwestern Iran and southern Iran within the past few years.
Azerbaijan*
;
Child
;
Female
;
Growth Charts
;
Head
;
Humans
;
Infant*
;
Infant, Newborn
;
Iran*
;
Parturition*
;
Weights and Measures
;
Child Health