Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

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

From |
Steve Samuels <sjsamuels@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Time-dependent variables and the simon & makuch method |

Date |
Wed, 23 Oct 2013 22:26:06 -0400 |

I've now had a chance to read the Simon and Makuch (1984) reference to a survival plot for use with a time-varying binary covariate that can change only once & in one direction. Their plot turns out to be identical to the "landmark" method published the year before by Anderson et al. (1983): one chooses a time point t*, and estimates survival curves that start at that point. The original stratum specific curves I showed are equivalent to setting the landmark at t* = 0. This is unrealistic if everyone starts out with the same value of the binary covariate. (That's not a problem for the Stanford heart transplant data, where 34 people were transplanted the day they enrolled.) The modification below shows how to to do the Anderson-Simon-Makuch curve for any landmark. I chose t* = 18 days, the median time to transplant in the Stanford data. ***********CODE BEGINS***************** webuse stan3, clear stset t1, fail(died) id(id) gen dummy=1 local lm = 18 /* landmark */ stcox dummy, strata(posttran), if _t>=`lm' predict surv, basesurv separate surv, by(posttran) tempvar t`lm' gen `t`lm'' = _t-`lm' twoway connect surv0 surv1 `t`lm'' if _t>=`lm', /// sort lp(dash solid) /// saving(g`"`lm'"', replace) /// title("Landmark = `lm' Days") *********CODE ENDS************* Obviously a -foreach- block could do the plots for several landmarks. References: Anderson, James R, Kevin C Cain, and Richard D Gelber. 1983. Analysis of survival by tumor response. Journal of Clinical Oncology 1, no. 11: 710-719, downloaded from: http://jco.publicaciones.saludcastillayleon.es/content/1/11/710.full.pdf Simon, Richard, and Robert W Makuch. 1984. A non‐parametric graphical representation of the relationship between survival and the occurrence of an event: Application to responder versus non‐responder bias. Statistics in Medicine 3, no. 1: 35-44. Steve sjsamuels@gmail.com On 11 October 2013 21:59, Steve Samuels wrote: Below I give the Mantel-Byar and Simon-Makuch references, with a pertinent review by Anderson et al. (1983). To answer your questions: • When data with time-varying covariates are properly -stset- as multiple-record data with the id() option, the log rank test in Stata *is* the Mantel-Byar test. • Replacement for KM plot In a reply to Nichole Boyle (http://www.stata.com/statalist/archive/2013-09/msg00408.html), I suggested a "future" conditional incidence function" for a binary time-dependent variable, and said I didn't know a reference. I do now. Anderson and colleagues published a version in 1983 and called it the "landmark method". They also criticized the use of the log rank test and advocated the use of the Mantel-Byar test. I don't have the Simon and Makuch reference, but here's a plot that gives a reasonable result in the Stanford heart transplant data (webuse stan3). It utilizes time-varying strata in the Cox model. The curve is akin to a synthetic life table in demography (e.g. Arias, 2010), in which current age-specific death rates are used to construct a life table. In this case, waiting time to transplant plays the role of age. The table has predictive value only if patients transplanted at _t and those transplanted earlier have similar risks of death for subsequent times. I'd expect dissimilar short term future risks, if only because of postoperative mortality. ***********CODE BEGINS***************** webuse stan3, clear stset t1, fail(died) id(id) sts test posttran, logrank // Mantel-Byar stcox posttran // p-values should be close to above /* -stcox- to get stratum-specific KM curves */ gen dummy=1 stcox dummy, strata(posttran) predict surv, basesurv separate surv, by(posttran) twoway connect surv0 surv1 _t, sort lp(dash solid) *********CODE ENDS************* References: Anderson, James R, Kevin C Cain, and Richard D Gelber. 1983. Analysis of survival by tumor response. Journal of Clinical Oncology 1, no. 11: 710-719, downloaded from: http://jco.publicaciones.saludcastillayleon.es/content/1/11/710.full.pdf Arias, E. 2010. United States life tables, 2006. Natl Vital Stat Rep 58, no. 21: 1-40 www.cdc.gov/nchs/data/nvsr/nvsr58/nvsr58_21.pdf Mantel, Nathan, and David P. Byar. 1974. Evaluation of Response-Time Data Involving Transient States: An Illustration Using Heart-Transplant Data. Journal of the American Statistical Association Journal of the American Statistical Association 69, no. 345: 81-86. Simon, Richard, and Robert W Makuch. 1984. A non‐parametric graphical representation of the relationship between survival and the occurrence of an event: Application to responder versus non‐responder bias. Statistics in Medicine 3, no. 1: 35-44. Steve > On Oct 9, 2013, at 6:51 AM, Florian Posch wrote: > > Dear Statalisters, > > your help would be very much appreciated on the following: > > I'm working on a dataset where I am modeling the impact of a time-dependent variable (the onset of thrombosis during follow-up) on survival. This analysis works fine with stsplit, and is pretty much the same as done in the Stanford Heart Transplant data example: > > The Stata Journal (2004) 4 , Number 2, pp. 221–222 > Stata tip 8: Splitting time-span records with categorical time-varying covariates > > Again, my analysis works well for the Cox model, Kaplan-Meier survival curves, and the logrank-test (as illustrated in the Staa journal paper above). However, some recent reviews postulate that time-dependent covariates can validly be used in the Cox model but that is is INAPPROPRIATE to use them in Kaplan-Meier survival curves and the logrank test. These reviews suggest that the appropriate substitute methods in this setting are the Simon & Makuch plot (substitute for Kaplan-Meier curves), and the Mantel-Byar test (substitute for the logrank test). > > Searching the web I found some posts in forums and a couple of papers on Pubmed which say that Stata has implemented these methods, however, I could not find such a package on the SSC or anywhere else in Stata. A prior post regarding this issue on statalist remained unanswered: > > http://www.stata.com/statalist/archive/2010-05/msg00079.html > > Do you know where I can find these analysis methods for Stata? > > Thank you very much in advance for your input! > > Flo > > Florian Posch, MSc > MD PhD Student > Medical University of Vienna > * * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Time-dependent variables and the simon & makuch method***From:*Florian Posch <florian.posch@meduniwien.ac.at>

- Prev by Date:
**Re: st: Why no error with -table- & trailing -if- ?** - Next by Date:
**st: Creating bar graph where cluster of bars is one variable rather than several variables in each cluster** - Previous by thread:
**Re: st: Time-dependent variables and the simon & makuch method** - Next by thread:
**Re: st: Time-dependent variables and the simon & makuch method** - Index(es):