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plored.
Results:For all cancer outcomes, a high genetic risk was associated
with an increased cancer risk, or there was a trend in that direction.
Those in the top PRS tertile had a greater than 2-fold increased risk
of colorectal cancer (HR[95%CI]¼2.18[1.90,2.49]), pancreatic can-
cer (2.39[1.71,3.32]) and lymphocytic leukemia (2.45[1.67,3.59]).
An unhealthy lifestyle was associated with a higher cancer risk for 8
cancer types, with strong relationships observed for lung
(3.41[2.76,4.20]), pancreatic (2.06[1.47,2.91]), bladder
(1.95[1.43,2.66]) and kidney cancers (1.90[1.43,2.54]). No interac-
tions between HLI and PRSs were detected (all interaction p-val-
ues>0.10).
Conclusions: Associations between lifestyle and cancer incidence did
not differ by genetic risk.
Key messages: A healthy lifestyle can reduce the risk of several can-
cers, even in those who are genetically predisposed to develop
cancer.
mote from a pregnancy. These findings should be used by physicians
to guide care of women diagnosed with pregnancy-associated
cancers.
Abstract #: 872
Novel approach to estimating sex differences
unconfounded by familial factors from studying male-
female twin pairs
Lucas Calais-Ferreira
1
, Everton Mendonc¸a
2
, Shuai Li
1,3
,
Marcos Barreto
2
, Martha Hickey
4
, Gillian Dite
1
, Paulo Ferreira
5
,
Katrina Scurrah
1
, John Hopper
1
1
Centre for Epidemiology and Biostatistics, Melbourne School of
Population and Global Health, The University of Melbourne,
Melbourne, Australia,
2
AtyImoLab, Computer Science Department,
Federal University of Bahia, Salvador, Brazil,
3
Centre for Cancer
Genetic Epidemiology, Department of Public Health and Primary
i40 International Journal of Epidemiology, 2021, Vol. 50, Supplement 1
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Care, University of Cambridge, Cambridge, United Kingdom,
4
Department of Obstetrics and Gynaecology, The University of
Melbourne, Melbourne, Australia,
5
Musculoskeletal Health
Research Group, Faculty of Health Sciences, The University of
Sydney, Sydney, Australia
Focus of Presentation: Males and females differ substantially in their
exposures and outcomes across the life-course. Previous research
into sex differences has been limited by an inability to account for
inter-individual differences in genetic factors and in their early-life
environment. Studying within male-female twin pair differences
offers a unique opportunity to address these weaknesses that has not
yet been exploited.
Findings: We studied linked health administrative data for 28,054
newborn Brazilian male-female twin pairs. Using random-effects lo-
gistic regression, we found that males had 1.61 (95% CI: 1.38–
1.90, P<0.001) times higher risk of early neonatal mortality (first 6
days of life) compared with their female co-twins, after adjusting
empirically for birthweight and matching for gestational age and, by
design, for unmeasured familial factors including on average 50% of
genetic factors.
From analysing within-pair differences in genome-wide DNA meth-
ylation in blood samples for 55 Australian adolescent male-female
twin pairs, we found that 1,227 DNA methylation sites were more
methylated in females while only 157 sites were more methylated in
males (P<10
-6
). We also found weak evidence suggesting that males
have older DNA-methylation-based biological age than females
(P¼0.2).
Conclusions/Implications: Sex differences not explained by familial
confounders exist for neonatal mortality in newborns and for DNA
methylation in blood during adolescence.
Key messages: Analysing the within-pair differences of male-female
twin pairs brings novel and important strengths to the study of sex
differences, helping mitigate bias from uncontrolled familial con-
founding caused by genetic and environmental factors.
thromboses, strokes and heart attacks. We investigated geographic
variation in diagnosis and survival for classic MPNs.
Methods: Data for classic MPNs were obtained from the Australian
Cancer Database. Leroux spatial models for incidence and survival
were fitted using CARBayes, WinBUGS via R and tests for spatial
clustering were conducted.
Results: The age-standardised incidence rate was 4.9 (95% CI: 4.8-
5.0) per 100,000 person-years during 2007-2016 with relative sur-
vival of 78% (77%, 79%) at 5 years after diagnosis.
Strong evidence of spatial variation in incidence was observed
(p <0.001), with incidence rates low in Tasmania (4.2 per 100,000
person-years, 95% CI: 3.5-5.0) and Western Australia (6.1, 5.6-6.6)
and high in Victoria (9.5, 9.2-9.9) and Queensland (10.6, 10.2-
11.1).
Differences between states and territories could not be explained by
population rates of genetic testing or the proportion of registered
cases with histological evidence.
Conclusions: Stark spatial differences in incidence rates of classic
MPNs suggest that varying diagnosis and registration patterns be-
tween states results in under-recognition, and potentially undertreat-
ment. It is imperative that reporting is consistent so that sound
evidence is available for efforts to reduce disparities in diagnosis and
management.
Key messages: Early identification of MPNs is crucial, however,
strong spatial geographical variation in incidence rates suggest diag-
nostic and notification practices may not be consistent across the
country.
1
b
b
International Journal of Epidemiology, 2021, Vol. 50, Supplement 1 i41
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