Literature DB >> 34170924

Comparison of the performances of survival analysis regression models for analysis of conception modes and risk of type-1 diabetes among 1985-2015 Swedish birth cohort.

Adeniyi Francis Fagbamigbe1,2,3, Emma Norrman4,5, Christina Bergh4,5, Ulla-Britt Wennerholm4,5, Max Petzold6.   

Abstract

The goal is to examine the risk of conception mode-type-1 diabetes using different survival analysis modelling approaches and examine if there are differentials in the risk of type-1 diabetes between children from fresh and frozen-thawed embryo transfers. We aimed to compare the performances and fitness of different survival analysis regression models with the Cox proportional hazard (CPH) model used in an earlier study. The effect of conception modes and other prognostic factors on type-1 diabetes among children conceived either spontaneously or by assisted reproductive technology (ART) and its sub-groups was modelled in the earlier study. We used the information on all singleton children from the Swedish Medical Birth Register hosted by the Swedish National Board of Health and Welfare, 1985 to 2015. The main explanatory variable was the mode of conception. We applied the CPH, parametric and flexible parametric survival regression (FPSR) models to the data at 5% significance level. Loglikelihood, Akaike and Bayesian information criteria were used to assess model fit. Among the 3,138,540 singletons, 47,938 (1.5%) were conceived through ART (11,211 frozen-thawed transfer and 36,727 fresh embryo transfer). In total, 18,118 (0.58%) of the children had type-1 diabetes, higher among (0.58%) those conceived spontaneously than the ART-conceived (0.42%). The median (Interquartile range (IQR)) age at onset of type-1 diabetes among spontaneously conceived children was 10 (14-6) years, 8(5-12) for ART, 6 (4-10) years for frozen-thawed embryo transfer and 9 (5-12) years for fresh embryo transfer. The estimates from the CPH, FPSR and parametric PH models are similar. There was no significant difference in the risk of type-1 diabetes among ART- and spontaneously conceived children; FPSR: (adjusted Hazard Ratio (aHR) = 1.070; 95% Confidence Interval (CI):0.929-1.232, p = 0.346) vs CPH: (aHR = 1.068; 95%CI: 0.927-1.230, p = 0.361). A sub-analysis showed that the adjusted hazard of type-1 diabetes was 37% (aHR = 1.368; 95%CI: 1.013-1.847, p = 0.041) higher among children from frozen-thawed embryo transfer than among children from spontaneous conception. The hazard of type-1 diabetes was higher among children whose mothers do not smoke (aHR = 1.296; 95%CI:1.240-1.354, p<0.001) and of diabetic mothers (aHR = 6.419; 95%CI:5.852-7.041, p<0.001) and fathers (aHR = 8.808; 95%CI:8.221-9.437, p<0.001). The estimates from the CPH, parametric models and the FPSR model were close. This is an indication that the models performed similarly and any of them can be used to model the data. We couldn't establish that ART increases the risk of type-1 diabetes except when it is subdivided into its two subtypes. There is evidence of a greater risk of type-1 diabetes when conception is through frozen-thawed transfer.

Entities:  

Year:  2021        PMID: 34170924      PMCID: PMC8232413          DOI: 10.1371/journal.pone.0253389

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  37 in total

1.  International Committee for Monitoring Assisted Reproductive Technology: world report on assisted reproductive technology, 2011.

Authors:  G David Adamson; Jacques de Mouzon; Georgina M Chambers; Fernando Zegers-Hochschild; Ragaa Mansour; Osamu Ishihara; Manish Banker; Silke Dyer
Journal:  Fertil Steril       Date:  2018-11       Impact factor: 7.329

2.  Breast cancer adjuvant therapy: time to consider its time-dependent effects.

Authors:  Ismail Jatoi; William F Anderson; Jong-Hyeon Jeong; Carol K Redmond
Journal:  J Clin Oncol       Date:  2011-05-09       Impact factor: 44.544

Review 3.  Prevalence of diabetes among immigrants in the Nordic countries.

Authors:  Per E Wändell; Axel Carlsson; Kristin H Steiner
Journal:  Curr Diabetes Rev       Date:  2010-03

4.  Early emergence of ethnic differences in type 2 diabetes precursors in the UK: the Child Heart and Health Study in England (CHASE Study).

Authors:  Peter H Whincup; Claire M Nightingale; Christopher G Owen; Alicja R Rudnicka; Ian Gibb; Catherine M McKay; Angela S Donin; Naveed Sattar; K George M M Alberti; Derek G Cook
Journal:  PLoS Med       Date:  2010-04-20       Impact factor: 11.069

Review 5.  The current application of the Royston-Parmar model for prognostic modeling in health research: a scoping review.

Authors:  Ryan Ng; Kathy Kornas; Rinku Sutradhar; Walter P Wodchis; Laura C Rosella
Journal:  Diagn Progn Res       Date:  2018-02-07

6.  Robustness of individual and marginal model-based estimates: A sensitivity analysis of flexible parametric models.

Authors:  Elisavet Syriopoulou; Sarwar I Mozumder; Mark J Rutherford; Paul C Lambert
Journal:  Cancer Epidemiol       Date:  2018-11-12       Impact factor: 2.984

7.  ART in Europe, 2015: results generated from European registries by ESHRE.

Authors:  C De Geyter; C Calhaz-Jorge; M S Kupka; C Wyns; E Mocanu; T Motrenko; G Scaravelli; J Smeenk; S Vidakovic; V Goossens
Journal:  Hum Reprod Open       Date:  2020-02-24

8.  A flexible alternative to the Cox proportional hazards model for assessing the prognostic accuracy of hospice patient survival.

Authors:  Branko Miladinovic; Ambuj Kumar; Rahul Mhaskar; Sehwan Kim; Ronald Schonwetter; Benjamin Djulbegovic
Journal:  PLoS One       Date:  2012-10-17       Impact factor: 3.240

9.  Trends in diabetes in pregnancy in Sweden 1998-2012.

Authors:  Helena E Fadl; David Simmons
Journal:  BMJ Open Diabetes Res Care       Date:  2016-08-11

10.  Parental Smoking and Risk of Childhood-onset Type 1 Diabetes.

Authors:  Maria C Magnus; German Tapia; Sjurdur F Olsen; Charlotta Granstrom; Karl Mårild; Per M Ueland; Øivind Midttun; Jannet Svensson; Jesper Johannesen; Torild Skrivarhaug; Geir Joner; Pål R Njølstad; Ketil Størdal; Lars C Stene
Journal:  Epidemiology       Date:  2018-11       Impact factor: 4.822

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.