Quantifying Maternal and Paternal Disease History Using Log-Rank Score with an Application to a National Cohort Study

Authors

  • Rui Feng Department of Biostatistics and Epidemiology, University of Pennsylvania, USA
  • Hersh Patel Department of Biology, University of Pennsylvania, USA
  • George Howard Department of Biostatistics, University of Alabama at Birmingham, USA

DOI:

https://doi.org/10.6000/1929-6029.2014.03.01.4

Keywords:

Family history, stroke, risk score, maternal effect, imprinting

Abstract

Both maternal and paternal disease history can be important predictors of the risk of common conditions such as heart disease or cancer because of shared environmental and genetic risk factors. Sometimes maternal and paternal history can have remarkably different effects on offspring’s status. The results are often affected by how the maternal and paternal disease histories are quantified. We proposed using the log-rank score (LRS) to investigate the separate effect of maternal and paternal history on diseases, which takes parental disease status and the age of their disease onset into account. Through simulation studies, we compared the performance of the maternal and paternal LRS with simple binary indicators under two different mechanisms of unbalanced parental effects. We applied the LRS to a national cohort study to further segregate family risks for heart diseases. We demonstrated using the LRS rather than binary indicators can improve the prediction of disease risks and better discriminate the paternal and maternal histories. In the real study, we found that the risk for stroke is closely related with maternal history but not with paternal history and that maternal and paternal disease history have similar impact on the onset of myocardial infarction.

Author Biographies

Rui Feng, Department of Biostatistics and Epidemiology, University of Pennsylvania, USA

Department of Biostatistics and Epidemiology

Hersh Patel, Department of Biology, University of Pennsylvania, USA

Department of Biology

George Howard, Department of Biostatistics, University of Alabama at Birmingham, USA

Department of Biostatistics

References

Bassett SS, Avramopoulos D, Fallin D. Evidence for parent of origin effect in late-onset Alzheimer disease. Am J Med Genet 2002; 114(6): 679-86. http://dx.doi.org/10.1002/ajmg.10648 DOI: https://doi.org/10.1002/ajmg.10648

Bjornholt JV, Erikssen G, Liestol K, Jervell J, Thaulow E, Erikssen J. Type 2 diabetes and maternal family history: an impact beyond slow glucose removal rate and fasting hyperglycemia in low-risk individuals? Results from 22.5 years of follow-up of healthy nondiabetic men. Diabetes Care 2000; 23(9): 1255-9. http://dx.doi.org/10.2337/diacare.23.9.1255 DOI: https://doi.org/10.2337/diacare.23.9.1255

McCuaig JM, Greenwood CM, Shuman C, Chitayat D, Murphy KJ, Rosen B, Armel SR. Breast and ovarian cancer: the forgotten paternal contribution. J Genet Couns 20(5): 442-9. DOI: https://doi.org/10.1007/s10897-011-9368-7

Soroko SB, Barrettconnor E, Edelstein SL, Kritzsilverstein D. Family History of Osteoporosis and Bone-Mineral Density at the Axial Skeleton - the Rancho-Bernardo Study. J Bone Mineral Res 1994; 9(6): 761-69. http://dx.doi.org/10.1002/jbmr.5650090602 DOI: https://doi.org/10.1002/jbmr.5650090602

Sun Y, Sherman M. Some permutation tests for survival data. Biometrics 1996; 52(1): 87-97. http://dx.doi.org/10.2307/2533147 DOI: https://doi.org/10.2307/2533147

Howard G, Koch GG. The Glm Log-Rank Test - General Linear Modeling of Log-Rank Scores as a Method of Analysis for Survival-Data. Commun Statistics-Simulation Comput 1990; 19(3): 903-17. http://dx.doi.org/10.1080/03610919008812897 DOI: https://doi.org/10.1080/03610919008812897

Feng R, McClure LA, Tiwari HK, Howard G. A new estimate of family disease history providing improved prediction of disease risks. Stat Med 2009; 28(8): 1269-83. http://dx.doi.org/10.1002/sim.3526 DOI: https://doi.org/10.1002/sim.3526

Bernstein IM, Plociennik K, Stahle S, Badger GJ, Secker-Walker R. Impact of maternal cigarette smoking on fetal

growth and body composition. Am J Obstet Gynecol 2000; 183(4): 883-6. http://dx.doi.org/10.1067/mob.2000.109103 DOI: https://doi.org/10.1067/mob.2000.109103

Doege K, Grajecki D, Zyriax BC, Detinkina E, Zu Eulenburg C, Buhling KJ. Impact of maternal supplementation with probiotics during pregnancy on atopic eczema in childhood--a meta-analysis. Br J Nutr 107(1): 1-6. DOI: https://doi.org/10.1017/S0007114511003400

De-Regil LM, Palacios C, Ansary A, Kulier R, Pena-Rosas JP. Vitamin D supplementation for women during pregnancy. Cochrane Database Syst Rev 2: CD008873.

van den Hooven EH, de Kluizenaar Y, Pierik FH, Hofman A, van Ratingen SW, Zandveld PY, et al. Chronic Air Pollution Exposure during Pregnancy and Maternal and Fetal C-reactive Protein Levels. The Generation R Study. Environ Health Perspect.

Shah R, Diaz SD, Arria A, Lagasse LL, Derauf C, Newman E, et al. Prenatal Methamphetamine Exposure and Short-Term Maternal and Infant Medical Outcomes. Am J Perinatol.

Singer LT, Moore DG, Fulton S, Goodwin J, Turner JJ, Min MO, Parrott AC. Neurobehavioral outcomes of infants exposed to MDMA (Ecstasy) and other recreational drugs during pregnancy. Neurotoxicol Teratol.

Honea RA, Swerdlow RH, Vidoni ED, Burns JM. Progressive regional atrophy in normal adults with a maternal history of Alzheimer disease. Neurology 76(9): 822-9. DOI: https://doi.org/10.1212/WNL.0b013e31820e7b74

Koch GG, Sen PK, Amara I. Log-rank scores, statistics, and tests. In Encyclopedia of Statistical Sciences, Kotz S, Johnson NL, Eds. John Wiley & Sons: New York, NY. 1985; pp. 136-142.

Koch GG, Sen PK, Amara I. Log-rank scores, statistics, and tests. In Encyclopedia of Statistical Sciences, Kotz S, Johnson NL, Eds. John Wiley & Sons: New York, NY. 1985; pp. 136-142.

Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA 2007; 297(6): 611-9. http://dx.doi.org/10.1001/jama.297.6.611 DOI: https://doi.org/10.1001/jama.297.6.611

Harrell FE, Lee KL Jr., Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15(4): 361-87. http://dx.doi.org/10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4 DOI: https://doi.org/10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4

Gonen M, Heller G. Concordance probability and discriminatory power in proportional hazards regression. Biometrika 2005; 92(4): 965-70. http://dx.doi.org/10.1093/biomet/92.4.965 DOI: https://doi.org/10.1093/biomet/92.4.965

Potapov S, Adler W, Schmid M. survAUC: Estimators of Prediction Accuracy for Time-to-Event Data 2011; Available from: http://cran.at.r-project.org/web/packages/survAUC/ index.html

Hsieh FY, Lavori PW. Sample-size calculations for the Cox proportional hazards regression model with nonbinary covariates. Control Clin Trials 2000; 21(6): 552-60. http://dx.doi.org/10.1016/S0197-2456(00)00104-5 DOI: https://doi.org/10.1016/S0197-2456(00)00104-5

Lloyd-Jones DM, Nam BH, D'Agostino RB, Levy D Sr., Murabito JM, Wang TJ, et al. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring. JAMA 2004; 291(18): 2204-11. http://dx.doi.org/10.1001/jama.291.18.2204 DOI: https://doi.org/10.1001/jama.291.18.2204

Sesso HD, Lee IM, Gaziano JM, Rexrode KM, Glynn RJ, Buring JE. Maternal and paternal history of myocardial infarction and risk of cardiovascular disease in men and women. Circulation 2001; 104(4): 393-8. http://dx.doi.org/10.1161/hc2901.093115 DOI: https://doi.org/10.1161/hc2901.093115

Ozanne EM, O'Connell A, Bouzan C, Bosinoff P, Rourke T, Dowd D, Drohan B, et al. Bias in the reporting of family history: implications for clinical care. J Genet Couns 21(4): 547-56. DOI: https://doi.org/10.1007/s10897-011-9470-x

Pal S. Prevalence of Selected Cardiovascular Diseases US Pharm 2009; 34(2): 2009. DOI: https://doi.org/10.4103/0970-0218.58389

Gehan EA. A Generalized Wilcoxon Test for Comparing Arbitrarily Singly-Censored Samples. Biometrika 1965; 52(1/2): 203-23. DOI: https://doi.org/10.2307/2333825

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Published

2014-01-31

How to Cite

Feng, R., Patel, H., & Howard, G. (2014). Quantifying Maternal and Paternal Disease History Using Log-Rank Score with an Application to a National Cohort Study. International Journal of Statistics in Medical Research, 3(1), 21–31. https://doi.org/10.6000/1929-6029.2014.03.01.4

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General Articles