Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Cameron McIntosh <cnm100@hotmail.com> |

To |
STATA LIST <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Parametric survival analysis with competing risks |

Date |
Sun, 29 Apr 2012 08:49:55 -0400 |

Correct -- the results will be biased if you use a naive Kaplan-Meier (censoring out the competing events as you say). Cox or Fine-Gray models are preferable in this case, but not perfect. Happy reading,Cam > Date: Sun, 29 Apr 2012 08:40:42 +0200 > From: enzo.coviello@tin.it > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Parametric survival analysis with competing risks > > Hi, > > thanks for the references. > Let me consider that none of the cited references recommend to apply the > ordinary survival regressions treating the subjects with competing > events as censored at the end of the study period. > > Enzo > > > > Il 28/04/2012 22.27, Cameron McIntosh ha scritto: > > Enzo, > > I also suggest you take a look at: > > > > Andersen, P.K., Geskus, R.B., de Witte, T.,& Putter, H. (2012). Competing risks in epidemiology: possibilities and pitfalls.International Journal of Epidemiology, Advance Access.http://ije.oxfordjournals.org/content/early/2012/01/08/ije.dyr213.abstracthttp://192.38.117.59/~pka/avepi11/Research_Report_11-2.pdf > > > > Dignam, J.T., Zhang, Q.,& Kocherginsky, M. (2012). The Use and Interpretation of Competing Risks Regression Models.Clinical Cancer Research, 18, 2301-2308. > > > > Dignam, J.T.,& Kocherginsky, M. (2008). Choice and Interpretation of Statistical Tests Used When Competing Risks Are Present. Journal of Clincial Oncology, 26(24), 4027-4034. > > > > Fine, J. P.,& Gray, R.J. (1999). A proportional hazards model for the subdistribution of a competing risk. Journal of theAmerican Statistical Association, 94(446), 496-509. > > > > Gichangi, A.,& Vach, W. (2005). The analysis of competing risks data: a guided tour. Statistics in Medicine, 132(4), 1-41. > > > > Lambert, P. C., Dickman, P. W., Nelson, C. P.,& Royston, P. (2010). Estimating the crude probability of death due to cancerand other causes using relative survival models. Statistics in Medicine, 29(7-8), 885-895. > > > > Williamson, P. R., Kolamunnage-Dona, R.,& Smith, C.T. (2007). The influence of competing-risks setting on the choice of hypothesis test for treatment effect. Biostatistics, 8(4), 689-694.http://biostatistics.oxfordjournals.org/content/8/4/689.full > > > > Putter, H., Fiocco, M.,& Geskus, R.B. (2007). Tutorial in biostatistics: competing risks and multi-state models. Statistics inMedicine, 26(11), 2389-2430.http://web.inter.nl.net/users/rgeskus/CompRisk.pdf > > > > Cam > > > >> Date: Sat, 28 Apr 2012 11:16:48 +0200 > >> From: enzo.coviello@tin.it > >> To: statalist@hsphsun2.harvard.edu > >> Subject: st: Parametric survival analysis with competing risks > >> > >> Dear Paul, > >> > >> In fact, since posting, I have read around& done some web searches& realised that survival analysis with competing risks is not so different from ordinary survival analysis, which answers my immediate problem . The same regression methods and software can apparently be used. It is only necessary to treat the subjects with competing events (women undergoing induction or C/S) as censored at the end of the study period. > >> > >> > >> I believe that ordinary survival regression can be applied to competing > >> risks situation if observations are appropriately weighted (Geskus, > >> Biometrics 2011 67, 39–49). > >> Unfortunately the very interesting approach proposed in the paper is not > >> currently available within Stata. > >> > >> Let me know if I should change this not encouraging point of view. > >> Best wishes. > >> > >> Enzo > >> > >> > >> -- > >> Enzo Coviello > >> Epidemiology Unit - Cancer Registry ASL BT > >> Piazza Umberto 1 > >> 76121 BARLETTA (BT) > >> Italy > >> mobile +39 347 5016016 > >> tel +39 0883 577329 > >> fax +39 0883 577288 > >> Home +39 0883 695055 > >> > >> > >> -- > >> Enzo Coviello > >> Epidemiology Unit - Cancer Registry ASL BT > >> Piazza Umberto 1 > >> 76121 BARLETTA (BT) > >> Italy > >> mobile +39 347 5016016 > >> tel +39 0883 577329 > >> fax +39 0883 577288 > >> Home +39 0883 695055 > >> > >> * > >> * For searches and help try: > >> * http://www.stata.com/help.cgi?search > >> * http://www.stata.com/support/statalist/faq > >> * http://www.ats.ucla.edu/stat/stata/ > > > > * > > * For searches and help try: > > * http://www.stata.com/help.cgi?search > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > > -- > Enzo Coviello > Epidemiology Unit - Cancer Registry ASL BT > Piazza Umberto 1 > 76121 BARLETTA (BT) > Italy > mobile +39 347 5016016 > tel +39 0883 577329 > fax +39 0883 577288 > Home +39 0883 695055 > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Parametric survival analysis with competing risks***From:*Enzo Coviello <enzo.coviello@tin.it>

**RE: st: Parametric survival analysis with competing risks***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: st: Parametric survival analysis with competing risks***From:*Enzo Coviello <enzo.coviello@tin.it>

- Prev by Date:
**Re: st: Actor-partner Interdependence Model data structure (redo)** - Next by Date:
**RES: st: pseudo panels implementation in Stata** - Previous by thread:
**Re: st: Parametric survival analysis with competing risks** - Next by thread:
**RE: st: Parametric survival analysis with competing risks** - Index(es):