25 aÑos de batalla contra el sida:...

25

AÑOS DE BATALLA CONTRA EL SIDA: 1983-2008

Alvaro Muñoz, PhDProfesor

de Epidemiologia

[y de Fabian Mendez]Cali,

2008.450

AMuñoz

y UniValle4

1983: Conferencia: The use of an autoregressive model for the analysis of longitudinal data in epistemiological studies.

4

1984: Goldberg MB, Guerrero R, Muñoz A. Mortalidad neonatal temprana en Cali. Un estudio de casos y controles. Colombia Medica

4

1985: Curso: Análisis de Estudios de Casos y Controles. Cali. Co-instructor con Norman Breslow.

4

1990: Co-institucion con Hopkins en beca de la Fogarty en SIDA4

1991: Curso: Epidemiologia del SIDA. PalmiraVinieron

de todas

partesdizque

a darsen

la buena

vidapero

resultaron

metidosen la epidemiologia

del sida

[por

SOspina]4

1992: Trujillo JM, Concha

M, Muñoz

A, Bergonzoli

G, Mora C, Borrero

I, Gibbs CJ, Jr., Arango

C. Seroprevalence

and cofactors of HTLV-I infection in Tumaco, Colombia. AIDS Res Hum Retroviruses

4

1993: Alzate A, Crespo MDP, Carrasquilla G, Corral R, Sánchez N, Muñoz A. PPD and HIV infection in Cali, Colombia. J Acquir Immune Defic Syndr

AMuñoz

y UniValle

(cont.) 4

2000: Méndez F, Carrasquilla G, Muñoz A. Risk factors associated with malaria infection in an urban setting. Trans R Soc Trop

Med Hyg

4

2002: Mendez F, Muñoz A, Carrasquilla G, Jurado D, Arevalo-

Herrera M, Cortese JF, Plowe CV. Determinants of treatment response to pyrimethamine-sulfadoxine

and subsequent transmission potential in non-severe falciparum

malaria. Am J Epidemiol

4

2004: Muñoz

N, Mendez F, Posso

H, Molano

M, van den Brule AJC, Ronderos

M, Meijer C, Muñoz

A, for the INC HPV Study Group. HPV infection. J Infect Dis

4

2005: Mendez F, Muñoz N, Posso H, Molano M, Moreno V, van den Brule AJC, Ronderos M, Maijer C, Muñoz A, for the INC HPV study group. Coinfection

with HPV types. J Infect Dis 4

2006: Mendez F, Muñoz

A, Plowe

CV. Use of area under the curve to characterize transmission potential after antimalarial

treatment. Am J of Tropical Med and Hygiene

4

2007: Mendez F, Herrera S, Murrain B, Gutierrez A, Moreno L, Manzano M, Muñoz A, Plowe C. Selection of Antifolate

resistant P. Falciparum

by Sulfadoxine-Pyrimethamine

treatment and infectivity to Anopheles Mosquitoes. Am J of Tropical Med & Hygiene

Epidemiologia

del VIH/SIDAInfeccion con HIVBiomarcadores•

Virologicos: Cantidad

del virus en la sangre

(copias/ml) •

Immunologicos: Grado

de immunodepresion

(conteo

de celulas

CD4 por

mm3)Intervenciones: terapia antiretroviral, profilaxis contra infecciones oportunisticasEventos clinicos: SIDAMuerte: tiempos de supervivencia

Distinguishing Efficacy, Individual and Population Effectiveness of Therapies

Muñoz

A, Gange

S, Jacobson LP. AIDS, 2000; 14:754-6.

6

Epidemiologic ConceptsMuñoz, Gange, Jacobson AIDS’00

Clinical TrialsObservational/Cohort Studies

Efficacy

Effectiveness

Individual Population[Efficiency]

Phillips et al., AIDS ’99Sabin et al., AIDS ’99

Benson et al., NEJM ’00Concato

et al., NEJM ’00

Hoover et al. Stat Med’94Detels

et al., JAMA ’98Porter et al., Lancet ’03

Schneider et al., AIDS’05Cox et al., Stat in Med’07Brenner et al., Lancet ’02

Cole et al., AJE ’03

Hammer et al., NEJM ’97Gulick

et al., NEJM ’97

Stukel

et al.,

JAMA’07

7

Concato

et al Conclusions4“The popular belief that only randomized,

controlled trials produce trustworthy results and that all observational studies are misleading does a disservice to patient care, clinical investigation, and the education of health care professionals.”

4“La creencia

popular de que

solamente ensayos

controlados

y con aleatorizacion

producen

resultados

fidedignos

y que

todos los estudios

observacionales

son engañosos

le sirve

negativamente

al cuidado

de pacientes, a la investigacion

clinica

y a la

educacion

de las

profesionales

de la salud”Source: N Engl J Med 2000, vol 342, p 1889

8

Setting / Study

Efficacy Clinical Trial

Individual Observational/Cohort Effectiveness

Population Observational/Cohort Effectiveness

9

Groups ComparedEfficacy Individual A-Treated

Individual B-Untreated

Individual Individual A-TreatedEffectiveness Individual B-Untreated

or Within individuals -

Pre-treatment compared to Post-treatment

Population Population A when most illEffectiveness are treated

compared toPopulation A when none

are treated

10

ComparabilityEfficacy Randomization

Individual Stratification/Regression; Effectiveness Inverse Probability Weights

Population Groups with similar Effectiveness times at risk

or Groups with similar markers at start of eras

11

Public Health Impact

Efficacy Results under controlled conditions

Individual Supplements (confirms) Effectiveness results of clinical trials

Population Complements clinical trials; Effectiveness Measures reduction of

disease burden resulting from treating subgroups at highest risk

12

Drawbacks

Efficacy Not necessarily applicableto “real world”

Individual Residual confounding due Effectiveness to selection by indication

Population Possible ecological Effectiveness fallaciousness

13

Use of Cohort Studiesfor Evaluating Effectiveness

of AIDS Therapies

14

Patterns of the Hazard of Death after AIDS through the

Evolution of Antiretroviral Therapy: 1984 -2004

Muñoz, Gange, Jacobson. AIDS; 2000

Schneider, Gange, …, Muñoz.

AIDS; 2005

15

Objective of analysis:In individuals with the same years since AIDS diagnosis and of the same age, type of AIDS and CD4 cell count at AIDS diagnosis, the hazard of death has quantitatively

and

qualitatively

changed in the HAART eras.

Objective

Years after AIDS diagnosis time axis

calendar exposure Age, Type of AIDS, CD4 cell count at diagnosis confounders

Death event

16

Progression of HIV-1 Infection prior to HAART

Muñoz, Xu. Stat Med ’96; Enger

et al. JAMA ’96; Jacobson et al. AJE ’93 -

Update

2.7

10.3

8.9 median1.3

5.3 5 percent

SC AIDSCD4≤

200 DEATHAIDS DEATH

1199/21371093/13131213/1620

Origin Event1.0

0.8

0.6

0.4

0.2

0.0

50 10 15Time in Years

Prop

ortio

n

October 1998

17

Calendar Time

Perc

ent R

ecei

ving

The

rapy

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

0102030405060708090100A

Calendar Time

Perc

ent R

ecei

ving

The

rapy

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

0102030405060708090100

Study Began in October 1994

B

MonotherapyCombination

Therapy

PI-HAART

NonPI-HAART

NonPI-HAART

PI-HAARTCombination Therapy

Monotherapy

Multicenter AIDS Cohort Study

Women’s Interagency HIV Cohort Study

Schneider, Gange,…, Muñoz. AIDS 2005

18

Periods

July 1984 –

Dec 1989 no/mono therapy

Jan 1990

–

Dec 1994 mono/combination

(dual)

Jan 1995

–

June 1998 HAART introduction

July 1998 –

June 2001 Short-term stable HAART

July 2001 –

Dec 2003 Moderate-term stable HAART

19

Number Seen

Incident AIDS Deaths

Period

1984.5 –

1990.0 633 100% 61%

1990.0 –

1995.0 660 100% 67%

1995.0 –

1998.5 472 100% 23%

1998.5 –

2001.5 496 29% 14%

2001.5 –

2004.0 464 12% 9%

Descriptive Statistics by Period

20

Person Visits

Median CD4

Median HIVRNA

Adherence <95%

Period

1984.5 –

1990.0 690 65 169,105 NA

1990.0 –

1995.0 1,173 37 175,198 NA

1995.0 –

1998.5 1,555 242 10,000 10%

1998.5 –

2001.5 2,131 317 2,274 24%

2001.5 –

2004.0 1,600 349 927 21%

Descriptive Statistics by Period (cont.)

21

Data Analysis Methods

Survival methods for staggered entries (i.e., at the start of a given period, those diagnosed in previous periods and alive enter “late” to the given period)

Calendar as external time-dependent exposure

Relative times : parametric (e.g., weibull) regression

1984.5 - 1990.0

0 2 4 6 8

020

040

060

01990.0 - 1995.0

0 2 4 6 8

020

040

060

0

1995.0 - 1998.5

0 2 4 6 8

020

040

060

0

1998.5 - 2001.5

0 2 4 6 8

020

040

060

0

2001.5 - 2004.0

0 2 4 6 8

020

040

060

0

1984.5 - 1990.0

0 2 4 6 8

020

040

060

0

633= 245 + 388 660= 215

+ 445

472= 363

+ 109

496= 425

+ 71

464= 420

+ 44

: 57 per 100 PY: 49 per 100 PY

: 14 per 100 PY

: 6 per 100 PY: 4 per 100 PY

23Years from AIDS diagnosis

Cum

ulat

ive

Mor

talit

y af

ter A

IDS

(%)

0

20

40

60

80

100

Kaplan-MeierWeibull

1st QuartileMedian

3rd Quartile

0 2 4 6 8

June 1984 –

Dec 1989($=0.55; F=0.90)

Jan 1990 –

Dec 1994($=0.70; F=0.81)

Jan 1995 –

June 1998($=2.48; F=1.53) July 1998 –

June 2001($=2.96; F=1.22)

July 2001 –

Dec 2003($=3.25; F=1.31)


24Years from AIDS Diagnosis

Haz

ard

of d

eath

afte

r AID

S (%

)

0

20

40

60

80

100

0 2 4 6 8

1st QuartileMedian

3rd Quartile

Therapy Era 1st

Quartile Median

Jun 1984 –

Dec 1989 0.6 years 1.2 years

Jan 1990 –


Jan 1995 –

Jun 1998 1.8 years 6.8 years

Jul 1998 –

Jun 2001 4.2 years 12.3 yearsJul 2001 –



25

A General Gamma-Based History of Survival after AIDS: 1984-2004

Cox C, Chu H, Schneider M, Muñoz

A. Parametric Survival Analysis and

Taxonomy of Hazard Functions for the Generalized Gamma Distribution.

Stat Med 2007;26:4352-74.

26

Parametric Models for Survival Data

•

Exponential, Weibull, lognormal, gamma, log logistic

• Do not require proportionality of hazards

•

Maximum likelihood for data with right, interval and left censoring; and data with late entries (truncation)

• Complete description of hazards

• Relative times and relative hazards

27

Challenges in Parametric Analysis of Survival Data

• Choosing among many alternatives

• Avoid being too restrictive (e.g., Weibull)

•

Family should incorporate hazards which are:

– increasing

– decreasing

– arc-shaped

– bathtub-shaped

28

• λ

→ 0 corresponds to Lognormal• λ

= 1 corresponds to Weibull

• Time at which p% fail:

Proportion surviving greater then time units:

where 1

0

1( ; )( )

z uz u e duγγγ

− −Γ =Γ ∫ is the Gamma c.d.f. with

mean and variance equal to

2 / 2

2 / 2

( ) 1 [ ( ) ; ] 0

[ ( ) ; ] 0GGS t e t

e t

β λ σ

β λ σ

λ λ λ

λ λ λ

− − −

− − −

= − Γ >

= Γ <

γ

Cox, Chu, Schneider, Muñoz. Stat Med 2007

Generalized Gamma Parameters: location, scale, shape $, F , 8

( )log[ ] log[ ( )]t p t pλβ σ= +where t ( ) is the pth percentile of the standard (0,1, )p GGλ λ

t

29

0 1 2 3

-1

0

1

2

3Shape (λ)

Scale (σ)

λ = σ

Gamma

Weibull

Lognormal

Ammag

Inverse Gamma 8 = -F

λ = 1/σ

Inverse Weibull

Inverse Ammag

8

= -1/F

Cox, Chu, Schneider, Muñoz. 2007 Stat Med

30Years from AIDS diagnosis

Cum

ulat

ive

Mor

talit

y af

ter A

IDS

(%)

0

20

40

60

80

100NonparametricGeneralized Gamma

0 1 2 3 4 5 6 7 8

July 1984 -

Dec 1989

Jan 1990 -

Dec 1994

Jan 1995 -

June 1998 July 1998 -

Dec 2003

Fit of the General Gamma vs. Nonparametric

31Cumulative Percent Deceased

Rel

ativ

e Ti

me

(Deciles for Period 1 : 0.23, 0.47, 0.72 years)

Period 2 to Period 1 Period 3 to Period 1 Period 4 to Period 1

Period 2: Jan1990-

Dec1994

Period1: Jul1984-

Dec1989

Period 3: Jan1995-

Jun1998

Period1: Jul1984-

Dec1989

Period 4: Jul1998-

Dec2003

Period1: Jul1984-

Dec1989

Relative Times Cox, Chu, …, Muñoz. Stat Med 2007

5

10

15

1

2

3

4

10 20 30

5

10

15

1

2

3

4

10 20 30

5

10

15

1

2

3

4

10 20 30


Rel

ativ

e Ti

me



Period 2: Jan1990-

Dec1994

Period1: Jul1984-

Dec1989

Period 3: Jan1995-

Jun1998

Period1: Jul1984-

Dec1989

Period 4: Jul1998-

Dec2003

Period1: Jul1984-

Dec1989


5

10

15

1

2

3

4

10 20 30

5

10

15

1

2

3

4

10 20 30

5

10

15

1

2

3

4

10 20 30


Rel

ativ

e Ti

me



5

10

15

1

2

3

4

10 20 30

5

10

15

1

2

3

4

10 20 30

5

10

15

1

2

3

4

10 20 30

Period 2: Jan1990-

Dec1994

Period1: Jul1984-

Dec1989

Period 3: Jan1995-

Jun1998

Period1: Jul1984-

Dec1989

Period 4: Jul1998-

Dec2003

Period1: Jul1984-

Dec1989


34

Software for the Doerswww.statepi.jhsph.edu/software

• STATA : streg

anc

and anc2

options allow general regression, not simply conventional

•SAS : PROC LIFEREG Conventional

PROC NLMIXED General

• S-plus: censorReg

nlminb

Cox, Chu, Schneider, Muñoz. 2007 Stat Med

35

Conclusions•

Parametric survival analysis based on the General gamma–

allows for different shapes of the hazard function from increasing to decreasing; from arc-type to bathtub.

–

provides a means to characterize the HISTORY of the survival after AIDS through the evolution of antiretroviral therapies.

–

enhances the power of the cohort design by linking epidemiology to public health via the assessment of population effectiveness.

–

directly estimates relative times, a measure of effect that facilitates wider communication of findings.

Reflecciones

con cara

al futuro4El SIDA como

enfermedad

cronica.

4La necesidad

imperativa

de ofrecer tratamiento

a individuos

infectados

con VIH e

indicados

a recibir

tratamiento

4Oportunidad

de un tratamiento

de tener efectos

de prevencion

pero

al mismo

tiempo

hacer

mas

dificil

elucidacion

de eficacia

de vacunas.

4El interes

de caracterizar

el envejecimiento con tratamiento

prolongado

contra el VIH.

TROVASPor

Sigifredo

Ospina;1991

Vinieron

de todas

partesdizque

a darsen

la buena

vidapero

resultaron

metidosen la epidemiologia

del sida

Se escogio

muy

bien

el sitiocon disenos

especialeses

un lugar

excelentepa' retiros

espirituales

Vinieron

las

presentacionesmucha

gente

conocidaprimer factor de riesgoen la epidemia

del sida

Empezo

pues

la academiano hubo

ningun

debatetodo

iba

muy

biencon carrasquilla

y alzate

CIAT, Palmira

SOspina, FdelaOz, VEspitia, LMGomez, EPMuñoz, AConcha, RCorral, JRodriguez, RRodriguez, FDelgado, RCarvajal, JMuñoz, MIGutierrez, MConcha,

Incidencia

y Prevalencia

El profe

antes de hablarde un poco

de garabatoslogro

mariar

todo

el grupomoviendo

los acetatos

Si era poco

importanteno pudimos

sabero era tan importanteque

no lo dejaba

ver

Pero

de todas

manerashabia

cosas

muy

raraslas

variables de reinaldoeran

muchisimo

mas

claras

Y a alguien

le dieron

titulolo bautizaron

el biologofrente

al microcomputadorya

quedaba

microbiologo

Para promover

la BUSQUEDA

Oh, Oh

Reinaldo

Carvajal

“no tiene

sentido

biologico”

Y llego

el segundo

diamuñoz

comenzo

primerono hubo

ni

una

preguntaquedamos

viendo

un chispero

Vino

un cambio

refrescantepues

todo

estaba

al revesqueriamos

que

nos

hablaran

claroy nos

hablaron

en ingles

Preguntaron

quien

no entiendey alguien

dijo

con enojosyo

le entiendo

muy

bien

al profepero

no le entiendo

a estos

patojos

El trabajo

se hizo

en grupostrabajamos

en tripletay por

mas

que

lo intentamosno pudimos

encontrar

el beta

Ken Nelson, el otro

“blanco”

Yours truly or “el paisa”

Estudiantes

preguntando

en ingles de juanchito

β

Las presentaciones

de sidano fueron

cosa

cualquieracon la primera

presentacionse armo

pues

la garrotera

Que

es

culpa del ministerioque

problemas

de tiempo

atrasmentiras

que

es

problemadel que

recibe

por

detras

Hablaron

bastante

pajaatacaron

sin compasiony a proposito

de pajaes

un factor de proteccion

Y en los casos

de sida

en Valleuna

verdad

muy

duradizque

no hay ni

un solo casoen el municipio

de Buenaventura

OR= 4.3

OR= 0.67

Mucha

paja?

Nadie

podia creeralguien

sabe

que

paso?alguien

tuvo

la respuestael colera

los mato

Chucho

alcanzo

la estrellay tomo

la iniciativanos

puso

a ver

en egretla epidemiologia

del sida

Hablaron

tambien

muy

claroy sin muchos

disimulosnos

entregan

la tareacasi

nos

vamos

de culos

Y ya

para

terminaryo

quiero

decir

adiosespero

volverlos

a veren el proximo

llamado

de dios.

Riesgos

Competitivos

Chucho

Rodriguez

A los 25 años

de la maestria en epidemiologia, UniValle:

2008.450

25 aÑos de batalla contra el sida:...

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