Roch Giorgi LERTIM EA3283, Faculty of Medicine, Mediterranean University, Marseille, France Estimation Methods for Relative

Roch Giorgi

LERTIM EA3283, Faculty of Medicine, Mediterranean University, Marseille, France

http://lertim.fr

Estimation Methods for Relative

Survival

Presentation and Perspective of the

MESURE ProjectMethods and Application for Population Based Survival

September 21, 2010 – Frascati

email: [email protected]

http://lertim.fr/

mailto:[email protected]

© Roch Giorgi, LERTIM, Faculty of Medicine, Mediterranean University 2

Context (1)

Large utilisation of relative survival approach to estimate cancer survival (population-based studies)

Models/Methods used may vary between research centres

New developments are challenges


Context (2)

General registrySpecialised registry

FRANCIMFrench Network of Cancers Registries


Context (3) Common cancer database

Service de Biostatistiques, Hospices Civils de Lyon (SBHCL)

French teams (some) involved in methodology / epidemiology of population-based survivalLaboratoire d’Enseignement et de Recherche sur le

Traitement de l’Information Médicale, Marseille (LERTIM)

SBHCLService de Biostatistique et Informatique Médicale,

Dijon (SBIM)Laboratoire d’Epidémiologie et de Santé Publique,

Strasbourg (LESP)


Context (4) French teams (some) involved in methodology / epidemiology

of population-based survival LERTIM, Marseille SBHCL, Lyon SBIM, Dijon LESP, Strasbourg

International teams (some) involved in methodology / epidemiology of population-based survivalNon Communicable Disease Epidemiology Unit,

London (NCDEU)Centro Nazionale di Epidemiologia, Instituto

Superior di Sanita, Roma (CNE)Department of Epidemiology and Biostatistics,

Montreal (DEP)


Context (5)

NCDEULondonNCDEULondon

CENRomaCENRoma

SBHCLLyonSBHCLLyon

DEPMontrealDEPMontreal

SBIMDijonSBIMDijon

LESPStrasbourgLESPStrasbourg

FRANCIM networkFRANCIM network

Estimation Methods for

Relative SurvivalMESURE Project

Creation of a research network involving methodologists, epidemiologists

LERTIMMarseilleLERTIMMarseille


MESURE: Overall Aim

To improve the current methods for estimating cancer survival

To define required specifications for production of large-scale cancer survival statistics useful in Public Health

To obtainmore accurate estimatescomparable information on cancer survival, on its

public health impact


Funding a Network of Methodologist!


Network Funding

Some failures…

2009: Grant from the French Institute for Public Health Research (IRESP): 8,000 euros (R. Giorgi)1st seminar (Paris)

2009: Grant from the French National Research Agency (ANR-09-BLAN-0357): 378,000 euros (R. Giorgi)

but

Let’s go to work!


Description of the Work

WP1:Comparison of the current methods

WP2: Extension/Development ofstatistical methods

WP2.1:Statistical researches

WP2.2:Statistical programs

WP3: Production of guidelines

5 Deliverables

12 Deliverables

1 Deliverables

12 Deliverables

2 Tasks

4 Tasks

1 Tasks

Management

36 months


Task 0: Project Management Coordinator of the Project: R. Giorgi

Coordination between partners Management of the project, with all the partners

Leader of a task Coordination of the specific researches for the task Respect concerning the schedule/deliverables

Organisation 2 meetings a year with all the partners/external members

(Lyon Oct. 2009; Marseille Apr. 2010; Paris Nov. 2010) Invited collaborators (E. Cambois, J. Stare, M. Pohar-Perme,

…) Deliverables

1. Report of progress (every 6 months)2. Report of the meetings (every 6 months)


WP1 – Task 1: Comparisons

Leader SBHCL

Partners SBIM, LERTIM, LESP, CNE, DEP

Objectives To highlight the methodological limits and the advantages of the existing models for relative survival analyses

Subtasks 1.Methodological comparisons2.Determination of data sets3.Analyses/real data

Deliverables

1.Description of the studied models2.Determination/Constitution data sets3.Comparison based on real data4.Report indicating limits/advantages


WP1 – Task 2: Recommendations

Leader SBIM

Partners SBHCL, LERTIM, LESP, FRANCIM, NCDEU, CNE, DEP

Objectives To give advices for users of such relative survival models in their practice

Subtasks None

Deliverables

1.Report indicating advices for users


WP2 – Task 3: Life Tables

Leader LERTIM

Partners SBIM, SBHCL, LESP, NCDEU, DEP

Objectives To assess the impact of the variable used to stratify the life tables for relative survival analyses

Subtasks 1. Life tables generation2.Survival data generation3.Analyses/simulated data4.Analyses/real data

Deliverables 1.Simulations results2.Real data application


WP2 – Task 4: Spatial Variations

Leader LERTIM

Partners SBHCL, SBIM, LESP, FRANCIM, CNE

Objectives To propose a relative survival model to analyse the geographical variations in cancer survival

Subtasks 1.Development of the model2.Survival data generation3.Analyses/simulated data4.Analyses/real data5.Specific statistical program

Deliverables 1.Model for spatial survival data2.Simulations results3.Real data applications4.Specific statistical program


WP2 – Task 5: Frailty

Leader SBHCL

Partners LERTIM, LESP, SBIM, FRANCIM, NCDEU, DEP

Objectives To take benefits from random effect framework in relative survival

Subtasks 1. Development of the model2. Comparison fixed/random effect3. Analyses/real data4. Specific statistical program

Deliverables 1.Flexible frailty relative survival model2.Comparison of fixed & random effect models3.Real data applications4.Specific statistical program


WP2 – Task 6: Statistical Programs

Leader LESP

Partners LERTIM, SBHCL, NCDEU, DEP

Objectives To propose a statistical package to perform relative survival analyses using approaches studied and developed in this project

Subtasks 1.Specific packages/Programming2.Assessment existing programs3.Common package/Language4.Common package/Programming

Deliverables

1.Specific programs for Tasks 4 to 62.Common statistical program


WP3 – Task 7: Synthesis

Leader FRANCIM

Partners LERTIM, SBHCL, SBIM, LESP, NCDEU, CNE, DEP

Objectives To produce guidelines for cancer survival analysis with population-base data

Subtasks None

Deliverables

1.Synthesis and recommendations


PlanningPlanning Task Description M 3 M 6 M 9 M 12 M 15 M 18 M 21 M 24 M 27 M 30 M 33 M 36

T0 Project Management

T1 Comparisons current methods

ST1.1 Methodological comparisons

ST1.2 Determination of data sets

ST1.3 Analyses/real data

T2 Recommendations

T3 Life tables

ST3.1 Life tables generation

ST3.2 Survival data generation

ST3.3 Analyses/simulated data


T4 Spatial variations

ST4.1 Development of the model

ST4.2 Survival data generation

ST4.3 Analyses/simulated data


ST4.5 Specific statistical program

T5 Frailty

ST5.1 Development of the model

ST5.2 Comparison fixed/random effect


ST4.4 Specific statistical program

T6 Statistical programs

ST6.1 Specific packages/Programming

ST6.2 Assessment existing programs

ST6.3 Common package/language

ST6.4 Common package/Programming

T7 Synthesis


PlanningPlanning

Task Deliverables Delivery date Partner in chargeT0 Project management D0.1 Biannual and final reports M6:M36 each 6M LERTIM

D0.2 Biannual meetings with report M6:M36 each 6M LERTIM

T1 Comparisons D1.1 Description of the studied models M3 SBHCL of current methods D1.2 Determination/Constitution datasets M6 SBHCL

D1.3 Comparisons based on real data M12 SBHCLD1.4 Report indicating limits/advantages M15 SBHCL

T2 Recommendations D2.1 Report indicating advices for users M18 SBIM

T3 Life tables D3.1 Simulations results M15 LERTIMD3.2 Real data application M18 LERTIM

T4 Spatial variations D4.1 Model for spatial survival data M18 LERTIMD4.2 Simulations results M27 LERTIMD4.3 Real data applications M30 LERTIMD4.4 Specific statistical program M30 LERTIM

T5 Frailty D5.1 Flexible frailty relative survival model M18 SBHCLD5.2 Comparison of fixed & random effect models M24 SBHCLD5.3 Real data applications M30 SBHCLD5.4 Specific statistical program M30 SBHCL

T6 Statistical Programs D6.1 Specific programs for Task 4 to 6 M30 LESPD6.2 Common statistical package M33 LESP

T7 Synthesis D7.1 Synthesis and recommendations M36 FRANCIM


Brief Point 2009-2010

Master’s degree in science C. Danieli: Comparison of methods for estimating net survival N. Graffeo: Assessment of the impact of variables used to

stratify the mortality tables involved in the analysis of relative survival

Communication A. Belot, R. Giorgi. Joint frailty excess hazard model for

recurrent events and death. 31th annual conference of International Society for Clinical Biostatistics, Montpellier, Septembre 2010.

2010-…PhD degree

N. Graffeo: Modelling spatial cancer survival with relative survival models

M. Mounier: Contribution of relative survival methods in the prognosis of follicular lymphomas


For the Future…

ANR grant for the MESURE projectFirst grantUseful to apply for other grant applications

Project open to other collaborators, funders…

Need toDeepen even more some tasksGo ahead on other themes Increase methodological / epidemiological

collaborations for cross-national comparisons with direct application for public health decision makers


MESURE Members

LERTIM – Marseille Roch Giorgi Catherine Jean Gaudart Nathalie Graffeo

SBHCL – Lyon Nadine Bossard Jacques Estève Laurent Remontet Aurélien Belot Laurent Roche

LESP - Strasbourg -> INRS - Nancy

Guy Hédelin

NCDEU – London Michel Coleman Bernard Rachet

CNE – Roma Franco Berrino Ricardo

Capocaccia DEP - Montreal

Michal Abrahamowicz

Amel Mahboubi

http://cybertim.timone.univ-mrs.fr/recherche/projets-recherche/MESURE

SBIM - Dijon Catherine Quantin Christine Binquet

FRANCIM Pascale Grosclaude Marc Colonna Valérie Jooste Anne-Marie Bouvier Morgane Mounier

[email protected]

Documents

Roch Giorgi LERTIM EA3283, Faculty of Medicine, Mediterranean University, Marseille, France Estimation Methods for Relative