Efficacy of routine viral load, CD4 cell count, and clinical monitoring of adults taking antiretroviral therapy in Rural Uganda Alex Coutinho MD MPH DTM&H Jonathan Mermin MD MPH et al CROI Boston, USA February 2008

Obstacles to rural HIV care Dispersed population with limited transportation Access to ART associated with cost of transport to health center Prices for ART drugs have decreased dramatically in Africa and other costs now significant barriers for patients Laboratory facilities often limited and testing expensive

Laboratory monitoring in HIV care Baseline CD4 cell count and viral load associated with prognosis CD4 cell count useful in determining eligibility for ART Viral load during ART associated with clinical outcomes Routine CD4 cell count and viral load every 3 months is norm in U.S. and Europe

Home-based AIDS Care Program Adds ART and TB to care and prevention package for 1,000 people with HIV Family VCT, basic care package and drug adherence ART provided to all eligible adults and children in household Weekly home visits by lay workers; no scheduled clinic visits after enrollment

HBAC monitoring evaluation Open cohort of 1,000 adults with HIV and their family members Weekly home visits CD4 cell counts Viral loads Weekly home visits CD4 cell counts Weekly home visits Arm AArm CArm B Severe morbidity and mortality at 3 years

Setting Kampala Study area Kampala Study area

Eligibility criteria CD4 cell count ≤ 250 cells/µL or WHO clinical stage III or IV Excluding isolated pulmonary TB AST or ALT <5 times upper limit of normal Creatinine clearance ≥25 ml/min Karnofsky Performance Score ≥40%

Antiretroviral regimens 1 st line was nevirapine, lamivudine, and stavudine Efavirenz for concomitant TB treatment 2 nd line was lopinovir/ritonovir, didanosine, and tenofovir

Data collection Viral load and CD4 collected quarterly Data collected from home visits, clinic visits and hospitalizations Clinical conference on all deaths, hospitalizations, opportunistic illnesses, abnormal labs and changes in ART regimens

Treatment failure definition First response adherence support Arm A –2 consecutive detectable viral loads However, if copies/ml and clinically well, could continue –CD4 cell count

Treatment failure for Arms B and C Arm B –Persistently declining CD4 count measured on two separate occasions –Clinical failure Arm C –Unintentional weight loss of >10% –CDC category C illness –Diarrhea or fever for >1 month without correctable cause –New or recurrent oral, esophageal, vaginal candidiasis

Analyses Kaplan-Meier analysis of time to first event of severe morbidity or mortality, and death alone Cox proportional hazard models Poisson regression analyses for hospitalizations, morbidity Intention-to-treat from date of randomization and per protocol from >90 days after initiating ART

Results 1116 ART-naïve individuals randomized 1094 started ART –8% WHO stage IV; 31% stage III Median follow-up 3 years –126 deaths (11.2%) 47% in first 3 months –148 AIDS-defining illnesses 57% in first 3 months 61 (5.8%) had 2 viral loads >500 copies/ml 28 (2.7%) changed to 2 nd line drugs

Participant characteristics at baseline Arm A Clinical monitoring CD4 counts +VL N= 368 Arm B Clinical monitoring CD4 cell counts N=371 Arm C Clinical monitoring N=377 P-value Median age in years373839P=0.96 Female (%)75% 67%P = 0.01 Median CD4 cell count (cells/ µL) 128 [ ]127 [ ]131 [ ]P=0.65 HIV viral load (copies/ml) Median [IQR] 233,000 [77, ,000] 201,000 {63, ,000] 210,000 [74, ,000] P=0.63 Depression Scale Depressed (23-60)148 (40%)169 (46%)153 (41%)P=0.59 Not depressed (0-22)205 (56%)189 (51%)208 (55%) Missing15 (4%)13 (4%)16 (4%)

Time to event of severe morbidity or mortality A vs. B p=0.27 B vs. C p=0.22 A vs. C p=0.02 Intention-to-treat Per protocol A vs. B p=0.46 B vs. C p=0.034 A vs. C p=0.004

Time to death A vs. B p=0.73 B vs. C p=0.36 A vs. C p=0.21 Intention-to-treatPer protocol A vs. B p=0.75 B vs. C p=0.14 A vs. C p=0.25

Cox proportional hazards model First morbidity or mortality event Number participants EventsFollow-up Time Rate per 100 PYO Adjusted Hazard Ratio Compared to A P-valueCompared to B P-value Arm A Arm B [ ] Arm C [ ] [ ] Intention-to-treat

Number participants EventsFollow-up Time Rate per 100 PYO Adjusted Hazard Ratio Compared to A P-valueCompared to B P-value Arm A Arm B [ ] Arm C [ ] [ ] Cox proportional hazards model First morbidity or mortality event Per protocol

Specific disease morbidity IRRp-value Tuberculosis C vs. A1.7 p=0.043 C vs. B1.7p=0.045 Pneumocystis jiroveci pneumonia C vs. A8.7 p=0.01 C vs. B17.2p=0.009 Cryptococcal disease C vs. A2.3p=0.044 C vs. B3.1p=0.013 Kaposi’s sarcoma C vs. A3.3p=0.07 C vs. B1.6p=0.39

Cox proportional hazards models comparison of mortality Intention-to-treat adjusted hazard ratio Arm C compared with A 1.58 ( ) p=0.07 Arm C compared with B 1.38 ( ) p=0.18 Arm B compared with A 1.14 ( ) p=0.60 Per protocol adjusted hazard ratio Arm C compared with A 1.58 ( ) p=0.14 Arm C compared with B 1.72 ( ) p=0.09 Arm B compared with A 1.23 ( ) p=0.43

Treatment failure Similar number of people with 2 viral loads >500 copies/ml per arm: Arm A: 16, Arm B: 26, Arm C: 19 Having viral loads >500 copies/ml was associated with increased severe morbidity or mortality (18% vs. 10%; p=0.049)

Response to treatment ≥2 viral loads >500 copies/ml after 90 days Of these, changed to 2 nd line Total changed to 2 nd line Changed to 2 nd line with detectable viral load Arm N (%) N A16 (5)7 (44)77 (100) B26 (8)4 (15)44 (100) C19 (5)2 (11)172 (12) ALL61 (6)13 (21)2813 (46%) 90% complete viral suppression at 1 year

Viral load response Arm AArm BArm CP-value Median viral load prior to change (copies/ml) Median viral load 6 months after change < Days with viral load >500 before change Median viral load prior to not changing Median viral load 6 month after not changing <

Arm C 15 people changed to 2 nd line therapy with undetectable viral load, all were changed because of AIDS-defining events: –Number of cases Cryptococcal disease6 Tuberculosis6 Kaposi’s Sarcoma4 Cervical cancer2 Cytomegalovirus1 Recurrent pneumonia1 All occurred >1 year after starting therapy

Why did Arms A and B do better? Not only because of earlier regimen change in failing patients – 500 copies changed –Adherence resulted in subsequent suppression Viral load and CD4 cell count monitoring detected adherence issues before the occurrence of morbidity or mortality Clinical criteria were poorly sensitive and poorly specific to detect adherence challenges

Conclusions All study arms performed well –1 year mortality in Arm C (9%) lower than all but one study in Africa Rates of viral suppression high Lay workers can effectively deliver drugs, support adherence, and monitor patients without scheduled clinic visits Supporting adherence is the important determinant of success

How should ART be monitored? Clinical monitoring alone was associated with increased rate of new AIDS-defining events and trend towards increased mortality Build laboratory capacity No benefit seen for adding quarterly viral load measurements to CD4 cell counts However there is need to determine long- term outcomes and cost-effectiveness

Acknowledgements Dr. David Moore Dr. Rebecca Bunnell Dr. Jordan Tappero Dr. Willy Were Dr. Paul Weidle Dr. Sam Malamba Dr. Elizabeth Madraa Dr. Robert Downing Paul Ekwaru Dr. Richard Degerman HBAC participants CDC-Uganda staff in Tororo and Entebbe Uganda Ministry of Health TASO Uganda Uganda PEPFAR Team CDC-Atlanta USAID OGAC DSMB