Abstract
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/m2 versus 18.5–<25 kg/m2 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/m2, 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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2281-2290 |
| Number of pages | 10 |
| Journal | International Journal of Cancer |
| Volume | 141 |
| Issue number | 11 |
| DOIs | |
| State | Published - Dec 1 2017 |
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Keywords
- breast cancer
- colorectal cancer
- methods
- mortality
- obesity
- survival
ASJC Scopus subject areas
- Oncology
- Cancer Research
Cite this
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 Women's Health Initiative. / 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; Cheng, Ting Yuan David; Chlebowski, Rowan T.; Saquib, Nazmus; Nassir, Rami; Anderson, Garnet; Caan, Bette J.
In: International Journal of Cancer, Vol. 141, No. 11, 01.12.2017, p. 2281-2290.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Methodological considerations for disentangling a risk factor's influence on disease incidence versus postdiagnosis survival
T2 - The example of obesity and breast and colorectal cancer mortality in the Women's Health Initiative
AU - Cespedes Feliciano, Elizabeth M.
AU - Prentice, Ross L.
AU - Aragaki, Aaron K.
AU - Neuhouser, Marian L.
AU - Banack, Hailey R.
AU - Kroenke, Candyce H.
AU - Ho, Gloria Y.F.
AU - Zaslavsky, Oleg
AU - Strickler, Howard
AU - Cheng, Ting Yuan David
AU - Chlebowski, Rowan T.
AU - Saquib, Nazmus
AU - Nassir, Rami
AU - Anderson, Garnet
AU - Caan, Bette J.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - 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/m2 versus 18.5–<25 kg/m2 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/m2, 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.
AB - 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/m2 versus 18.5–<25 kg/m2 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/m2, 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.
KW - breast cancer
KW - colorectal cancer
KW - methods
KW - mortality
KW - obesity
KW - survival
UR - http://www.scopus.com/inward/record.url?scp=85030690146&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030690146&partnerID=8YFLogxK
U2 - 10.1002/ijc.30931
DO - 10.1002/ijc.30931
M3 - Article
C2 - 28833074
AN - SCOPUS:85030690146
VL - 141
SP - 2281
EP - 2290
JO - International Journal of Cancer
JF - International Journal of Cancer
SN - 0020-7136
IS - 11
ER -