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ZAMSTAR restricted randomisation CREATE Investigators Meeting 2005. Charalambos (Babis) Sismanidis LSHTM. ZAMSTAR overview. Zambia and South Africa tuberculosis and AIDS reduction study 24 communities (16 in Zambia, 8 in SA) are randomised in 4 arms (2x2 factorial).
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ZAMSTAR restricted randomisation CREATE Investigators Meeting 2005 Charalambos (Babis) Sismanidis LSHTM
ZAMSTAR overview • Zambia and South Africa tuberculosis and AIDS reduction study • 24 communities (16 in Zambia, 8 in SA) are randomised in 4 arms (2x2 factorial). • Primary outcome: culture +ve TB prevalence (survey on 5,000 patients sampled in each cluster) after 3 years of intervention application
Description of interventions • TB/HIV @ clinic • Strengthened DOTS • VCT TB/HIV at health centre access (offering IPT) • Basic HIV care • HIV prevention (condoms, STI management) • Enhanced Tuberculosis Case Finding (ECF) • Open access to sputum smear at health centre • Schools education campaign • Community mobilisation and mobile tuberculosis laboratory • Household level TB & HIV combined activities (HH) • Household counsellor visiting all TB households • Household members encouraged to test for HIV • TB preventive therapy for HIV+ve and children <6 • Both ECF & HH
ZAMSTAR primary aims • Does enhanced tuberculosis case finding (ECF) by a strategy of community mobilisation and improved access to sputum microscopy, reduce prevalence of tuberculosis in the community? • Do combined TB/HIV activities at the household level (HH), reduce prevalence of tuberculosis? • Does ECF plus HH (ECF+HH), yield additional benefits for tuberculosis control through additional case detection, improved case holding, treatment/prophylaxis of latent infection and reduction in HIV incidence?
Does ECF reduce the prevalence of tuberculosis in the community?
Does HH reduce the prevalence of tuberculosis in the community?
Stratification • The 24 clusters are stratified by country of cluster origin. 16 from Zambia, 8 in SA • Randomisation will be performed separately for each of the two strata
Zambia – Step I • 4 equally numbered groups of As, Bs, Cs & Ds to form from 16 available communities (i.e. 4 communities in each group). • Arm A will include 4 communities out of the 16: 16!/12!4! = 1820 choicesArm B another 4 from the remaining 12 communities: 12!/8!4! = 495 choicesArm C another 4 from the remaining 8: 8!/4!4! = 70 choicesArm D 4 from the remaining 4: 4!/4!0! = 1 choice • This amounts to=1820*495*70*1=63,063,000
Zambia – Step II • BUT since we do not have a fixed sequence by which intervention arms will be picked (sequence ABCD is a generic example) we need to multiply the previous total by 4! (i.e. all possible permutations for an array of 4 elements). • TOTAL: 63,063,000*4! = 1,513,512,000
South Africa – Step I • 4 equally numbered groups (= intervention arms) of As, Bs, Cs & Ds to form from 8 available communities (i.e. 2 communities in each group). • Arm A will have 2 communities out of 8 = 8!/6!2! = 28 choicesArm B another 2 from the remaining 6 communities (6!/4!2!) = 15 choicesArm C another 2 from the remaining 4 = 4!/2!2! = 6 choicesArm D 2 from the remaining 2 = 1 choice • Which amounts to = 28*15*6*1=2520
South Africa – Step II • Similarly since we do not have a fixed sequence by which intervention arms will be picked we need to multiply the previous total by 4! • TOTAL: 2520*4! = 2520*24 = 60,480
Computational headaches • Because of the very large number of possible permutations it has not so far been possible to list them all • Single file size not allowed to be >12GB • Current code produces multiple identical observations (which are then dropped)
Restricting randomisation • Possible restrictions: • HIV prevalence • TB infection (TST in children) • Open/Closed communities (Social Science) • Political restrictions (not all clusters in a community in the control arm-should this be extended to all arms?)
Changing lanes • THRio approach? • Instead of listing all possible permutations to get the exact proportion by which randomisation is restricted, I will now be randomly drawing a set number of permutations to estimate this proportion. • Then randomly draw one permutation from a list of ‘acceptable’ ones