BACKGROUND: Nowadays, the fact that cancers can aggregate in families is generally accepted. The aim of this study was to complete a comprehensive analysis of cancer-survival concordance in parents and their children diagnosed with the same cancer. METHODS: We used a population-based Swedish family database, that included about three million families and data for more than a million individuals with cancer. We analysed survival in children in relation to parental survival by use of the Kaplan-Meier method. We then modelled the risk in children in relation to parental survival by use of two multivariate proportional hazard (Cox) models adjusting for possible confounders of survival. FINDINGS: In our univariate Kaplan-Meier analysis, children with the same cancer as their parent and whose parent had died within 10 years of diagnosis showed significantly worse survival for breast (log rank p=0.01), colorectal (p=0.04), and prostate cancer (p=0.05) than those whose parents were alive at 10 years from diagnosis. By use of Cox modelling, we noted an increased hazard ratio for death from cancer in children with poor parental survival compared with those with good parental survival for colorectal cancer (hazard ratio [HR] 1.44 [95% CI 1.01-2.01]), lung cancer (1.39 [1.00-1.94]), breast cancer (1.75 [1.13-2.71]), ovarian cancer (2.23 [0.78-6.34]), and prostate cancer (2.07 [1.13-3.79]). All hazard-ratio estimates, except for ovarian cancer, were significant, with significant trends of increasing risk of death in children by degree of worsening survival outcome in parents defined in quartiles of survival (ie, good [best quartile], expected [middle two quartiles], or poor [worst quartile]). INTERPRETATION: Our findings suggest that cancer-specific survival in parents predicts survival from the same cancer in their children. Consequently, data on survival in a parent might have the potential to guide treatment decisions and genetic counselling. Finally, molecular studies to highlight the genetic determinants of cancer survival are now warranted.
BACKGROUND: Nowadays, the fact that cancers can aggregate in families is generally accepted. The aim of this study was to complete a comprehensive analysis of cancer-survival concordance in parents and their children diagnosed with the same cancer. METHODS: We used a population-based Swedish family database, that included about three million families and data for more than a million individuals with cancer. We analysed survival in children in relation to parental survival by use of the Kaplan-Meier method. We then modelled the risk in children in relation to parental survival by use of two multivariate proportional hazard (Cox) models adjusting for possible confounders of survival. FINDINGS: In our univariate Kaplan-Meier analysis, children with the same cancer as their parent and whose parent had died within 10 years of diagnosis showed significantly worse survival for breast (log rank p=0.01), colorectal (p=0.04), and prostate cancer (p=0.05) than those whose parents were alive at 10 years from diagnosis. By use of Cox modelling, we noted an increased hazard ratio for death from cancer in children with poor parental survival compared with those with good parental survival for colorectal cancer (hazard ratio [HR] 1.44 [95% CI 1.01-2.01]), lung cancer (1.39 [1.00-1.94]), breast cancer (1.75 [1.13-2.71]), ovarian cancer (2.23 [0.78-6.34]), and prostate cancer (2.07 [1.13-3.79]). All hazard-ratio estimates, except for ovarian cancer, were significant, with significant trends of increasing risk of death in children by degree of worsening survival outcome in parents defined in quartiles of survival (ie, good [best quartile], expected [middle two quartiles], or poor [worst quartile]). INTERPRETATION: Our findings suggest that cancer-specific survival in parents predicts survival from the same cancer in their children. Consequently, data on survival in a parent might have the potential to guide treatment decisions and genetic counselling. Finally, molecular studies to highlight the genetic determinants of cancer survival are now warranted.
Authors: Molly Scannell Bryan; Maria Argos; Irene L Andrulis; John L Hopper; Jenny Chang-Claude; Kathleen Malone; Esther M John; Marilie D Gammon; Mary Daly; Mary Beth Terry; Saundra S Buys; Dezheng Huo; Olofunmilayo Olopade; Jeanine M Genkinger; Farzana Jasmine; Muhammad G Kibriya; Lin Chen; Habibul Ahsan Journal: Breast Cancer Res Treat Date: 2017-05-13 Impact factor: 4.872
Authors: Albert Tenesa; Evropi Theodoratou; Farhat V N Din; Susan M Farrington; Roseanne Cetnarskyj; Rebecca A Barnetson; Mary E Porteous; Harry Campbell; Malcolm G Dunlop Journal: Clin Cancer Res Date: 2010-07-13 Impact factor: 12.531
Authors: Daniel C Koboldt; Krishna L Kanchi; Bin Gui; David E Larson; Robert S Fulton; William B Isaacs; Aldi Kraja; Ingrid B Borecki; Li Jia; Richard K Wilson; Elaine R Mardis; Adam S Kibel Journal: Cancer Epidemiol Biomarkers Prev Date: 2016-08-02 Impact factor: 4.254
Authors: Roelof Koster; Orestis A Panagiotou; William A Wheeler; Eric Karlins; Julie M Gastier-Foster; Silvia Regina Caminada de Toledo; Antonio S Petrilli; Adrienne M Flanagan; Roberto Tirabosco; Irene L Andrulis; Jay S Wunder; Nalan Gokgoz; Ana Patiño-Garcia; Fernando Lecanda; Massimo Serra; Claudia Hattinger; Piero Picci; Katia Scotlandi; David M Thomas; Mandy L Ballinger; Richard Gorlick; Donald A Barkauskas; Logan G Spector; Margaret Tucker; D Hicks Belynda; Meredith Yeager; Robert N Hoover; Sholom Wacholder; Stephen J Chanock; Sharon A Savage; Lisa Mirabello Journal: Int J Cancer Date: 2017-12-23 Impact factor: 7.396
Authors: Alice S Whittemore; Beth Stearman; Vickie Venne; Jerry Halpern; Anna Felberg; Valerie McGuire; Mary Daly; Saundra S Buys Journal: Breast Cancer Res Treat Date: 2009-03-19 Impact factor: 4.872
Authors: Jianfeng Xu; Siqun Lilly Zheng; Sarah D Isaacs; Kathleen E Wiley; Fredrik Wiklund; Jielin Sun; A Karim Kader; Ge Li; Lina D Purcell; Seong-Tae Kim; Fang-Chi Hsu; Pär Stattin; Jonas Hugosson; Jan Adolfsson; Patrick C Walsh; Jeffrey M Trent; David Duggan; John Carpten; Henrik Grönberg; William B Isaacs Journal: Proc Natl Acad Sci U S A Date: 2010-01-11 Impact factor: 11.205
Authors: Fredrik E Wiklund; Hans-Olov Adami; Sigun L Zheng; Pär Stattin; William B Isaacs; Henrik Grönberg; Jianfeng Xu Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-05 Impact factor: 4.254