Golden standard?

Golden standard?

Time-to-event data analyses Differences in methods routinely used by Regulators and HTA Anja Schiel, PhD Statistician / Norwegian Medicines Agency Disclaimer

The views and opinions expressed in this presentation are the author's own and do not necessarily reflect the official position of the Norwegian Medicines Agency or EMA. Time-to-event, whats so special? We censor patients to allow the use of their information despite not having observed the event of interest.

In this situation standard logistic regression is not appropriate. We need to keep in mind that Time-to-event must be positive (> 0) and is right skewed The probability of surviving past a certain point in time in itself is important information maybe more than observing the event What kind of assumptions we make and which estimators we use

Regulators Regulatory decision making is based on median survival times and HR The data

..and what we make of it HTA / Cost-effectiveness analysis Less interested in point estimators or the HR, but rather the area under the curve to allow Markov-modelling Models should run with a lifetime horizon to capture all relevant differences

HTA / Cost-effectiveness analysis Less interested in point estimators or the HR, but rather the area under the curve to allow Markov-modelling Models should run with a lifetime horizon to capture all relevant differences

HTA / Cost-effectiveness analysis Less interested in point estimators or the HR, but rather the area under the curve to allow Markov-modelling Models should run with a lifetime horizon to capture all relevant differences HTA / Cost-effectiveness analysis

Less interested in point estimators or the HR, but rather the area under the curve to allow Markov-modelling Models should run with a lifetime horizon to capture all relevant differences How to get from this..

.to this? Main problems for Regulators and HTAs is Decreasing follow-up time, in particular for OS Uncertainty with decreasing numbers of subjects at risk The solution used by the HTAs

Extrapolation by parametric modelling Solves the problem of the median point estimator, we get mean survival times Allows prediction beyond the actual observation time Can help with artefacts such as the staircase phenomenon

The challenge Find the appropriate parametric model The usual suspects:

Exponential Weibull Log-logistic Log-normal

Gompertz Generalised gamma Proportional hazard model or Accelerated Failure time model? The overlooked problem The assumption of proportional hazard

The treatment effect is constant over time in the observed but also the un-observed period This assumption needs to be tested! Regulators do not routinely ask for confirmation of the PH assumption HTAs start to request better documentation for the choice of modelling approach

Keep in mind .that this is not just a statistical exercise Biology Underlying risk

Choice of distributions Fit Validation /

Plausibility Best fit DSU TSD 14 Simple doesnt always work

More complex but also more flexible models exist There is no wrong or right by definition Is this just some sort of voodoo?

No, it will not make our decisions better, but it will make them better informed

Recently Viewed Presentations

  • Chapter 13

    Chapter 13

    In China no ratings were based on market performance ratings or credit scoring models such as KMV or CreditMetrics alone. Survey by Edwards and Luwia (2011) found all 60 credit rating agencies and credit advisory institutions in China used judgemental...
  • The Post Colonial Critic - Ms. Irandoust's Classes

    The Post Colonial Critic - Ms. Irandoust's Classes

    The Post Colonial Critic (1990s-present). Focuses on the literature produced by both the colonizers and the colonized. Explores the effects of colonization, including social, economic, political, religious effects, and specifically, explores the suffering of colonial cultures
  • Treatment of Diabetes in People with Heart Failure

    Treatment of Diabetes in People with Heart Failure

    Key Changes. New information on. The use of DPP4 inhibitor and GLP1 receptor agonists in people with type 2 diabetes and heart failure. Role of SGLT2 inhibitor in patients with established CVD to reduce heart failure hospitalization
  • Physics in the first year of CMS - moby.mib.infn.it

    Physics in the first year of CMS - moby.mib.infn.it

    MCWS - Frascati 24 Ottobre 2006 La Fisica nel primo anno di CMS Roberto Tenchini INFN - Pisa
  • Byron Nelson High School

    Byron Nelson High School

    Byron Nelson is a C2G Model School, and we will do all that we can to ensure your student is ready for college & career, the global workplace, and personal success. ... Melissa Whitfield - Records Manager . Mayda Duron...
  • Diapositiva 1 - SIMEU

    Diapositiva 1 - SIMEU

    Vaptans can improve cognitive function, enhance diuresis, and improve hemodynamics. These agents are generally well tolerated with a low side effect profile. The effects on survival and other outcomes in hyponatremic heart failure patients are uncertain and we await the...
  • Color Template Lt Gray - FHWA Operations

    Color Template Lt Gray - FHWA Operations

    [email protected] 202 366 1301 ... Association of State Highway and Transportation Officials AASHTO Office of the Federal Coordinator for Meteorology Sam Williamson OFCM FHWA Road Weather Program Other USDOT Agencies FAA, FTA, FRA, RSPA, USCG FEMA George Schoene Al Benet...
  • ELECTRICAL TECHNOLOGY B.L THERAJA A.K THERAJA 41 rights

    ELECTRICAL TECHNOLOGY B.L THERAJA A.K THERAJA 41 rights

    Gauss* Law. These equations are useful in the solution of many problems concerning electrostatics especially the problem of space charge* present in an electronic valve. The two equations can be derived by applying Gauss's theorem. ... If, for example, a...