Premium
Methodological considerations for disentangling a risk factor's influence on disease incidence versus postdiagnosis survival: The example of obesity and breast and colorectal cancer mortality in the W omen's H ealth I nitiative
Author(s) -
Cespedes Feliciano Elizabeth M.,
Prentice Ross L.,
Aragaki Aaron K.,
Neuhouser Marian L.,
Banack Hailey R.,
Kroenke Candyce H.,
Ho Gloria Y.F.,
Zaslavsky Oleg,
Strickler Howard D.,
Cheng TingYuan David,
Chlebowski Rowan T.,
Saquib Nazmus,
Nassir Rami,
Anderson Garnet,
Caan Bette J.
Publication year - 2017
Publication title -
international journal of cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.475
H-Index - 234
eISSN - 1097-0215
pISSN - 0020-7136
DOI - 10.1002/ijc.30931
Subject(s) - medicine , incidence (geometry) , colorectal cancer , breast cancer , risk factor , obesity , disease , oncology , surgery , gynecology , cancer , physics , optics
Often, studies modeling an exposure's influence on time to disease‐specific death from study enrollment are incorrectly interpreted as if based on time to death from disease diagnosis. We studied 151,996 postmenopausal women without breast or colorectal cancer in the Women's Health Initiative with weight and height measured at enrollment (1993–1998). Using Cox regression models, we contrast hazard ratios (HR) from two time‐scales and corresponding study subpopulations: time to cancer death after enrollment among all women and time to cancer death after diagnosis among only cancer survivors. Median follow‐up from enrollment to diagnosis/censoring was 13 years for both breast (7,633 cases) and colorectal cancer (2,290 cases). Median follow‐up from diagnosis to death/censoring was 7 years for breast and 5 years for colorectal cancer. In analyses of time from enrollment to death, body mass index (BMI) ≥ 35 kg/m 2 versus 18.5–<25 kg/m 2 was associated with higher rates of cancer mortality: HR = 1.99; 95% CI: 1.54, 2.56 for breast cancer ( p trend <0.001) and HR = 1.40; 95% CI: 1.04, 1.88 for colorectal cancer ( p trend = 0.05). However, in analyses of time from diagnosis to cancer death, trends indicated no significant association (for BMI ≥ 35 kg/m 2 , HR = 1.25; 95% CI: 0.94, 1.67 for breast [ p trend = 0.33] and HR = 1.18; 95% CI: 0.84, 1.86 for colorectal cancer [ p trend = 0.39]). We conclude that a risk factor that increases disease incidence will increase disease‐specific mortality. Yet, its influence on postdiagnosis survival can vary, and requires consideration of additional design and analysis issues such as selection bias. Quantitative tools allow joint modeling to compare an exposure's influence on time from enrollment to disease incidence and time from diagnosis to death.