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. 2012 Feb 22;2012:375217. doi: 10.1155/2012/375217

Loss to Followup in HIV-Infected Patients from Asia-Pacific Region: Results from TAHOD

Jialun Zhou 1, Junko Tanuma 2, Romanee Chaiwarith 3, Christopher K C Lee 4, Matthew G Law 1,*, Nagalingeswaran Kumarasamy 5, Praphan Phanuphak 6, Yi-Ming A Chen 7, Sasisopin Kiertiburanakul 8, Fujie Zhang 9, Saphonn Vonthanak 10, Rossana Ditangco 11, Sanjay Pujari 12, Jun Yong Choi 13, Tuti Parwati Merati 14, Evy Yunihastuti 15, Patrick C K Li 16, Adeeba Kamarulzaman 17, Van Kinh Nguyen 18, Thi Thanh Thuy Pham 19, Poh Lian Lim 20
PMCID: PMC3296146  PMID: 22461979

Abstract

This study examined characteristics of HIV-infected patients in the TREAT Asia HIV Observational Database who were lost to follow-up (LTFU) from treatment and care. Time from last clinic visit to 31 March 2009 was analysed to determine the interval that best classified LTFU. Patients defined as LTFU were then categorised into permanently LTFU (never returned) and temporary LTFU (re-entered later), and these groups compared. A total of 3626 patients were included (71% male). No clinic visits for 180 days was the best-performing LTFU definition (sensitivity 90.6%, specificity 92.3%). During 7697 person-years of follow-up, 1648 episodes of LFTU were recorded (21.4 per 100-person-years). Patients LFTU were younger (P = 0.002), had HIV viral load ≥500 copies/mL or missing (P = 0.021), had shorter history of HIV infection (P = 0.048), and received no, single- or double-antiretroviral therapy, or a triple-drug regimen containing a protease inhibitor (P < 0.001). 48% of patients LTFU never returned. These patients were more likely to have low or missing haemoglobin (P < 0.001), missing recent HIV viral load (P < 0.001), negative hepatitis C test (P = 0.025), and previous temporary LTFU episodes (P < 0.001). Our analyses suggest that patients not seen at a clinic for 180 days are at high risk of permanent LTFU, and should be aggressively traced.

1. Introduction

Loss to followup (LTFU) in patients receiving antiretroviral therapy can cause serious consequences such as discontinuation of treatment and increased risk of death [13]. At a program level, LTFU can make it difficult to evaluate outcomes of treatment and care [4, 5]. In resource-limited settings, where treatment has become rapidly available following the rollout of antiretroviral therapy, LTFU presents even more challenging obstacles that require special consideration and approaches [6, 7].

One of the key questions in patient followup is how to define a patient as LTFU. This has varied in studies conducted in different settings [810]. Defining LTFU using a very early threshold, for example, a patient with no clinic visit in the last three months, may result in many patients being considered as LTFU who would return to clinic naturally at a later date. Defining LTFU with a long threshold, for example, one year, may mean delaying too long before any effort is made to track patients potentially at risk of LTFU.

The majority of research into LTFU in HIV-infected patients receiving antiretroviral treatment in resource-limited settings has been conducted in the sub-Saharan Africa region [3, 1013]. A few studies have been conducted among Asian, mostly female, patients [1416]. Using data from the TREAT Asia HIV Observational Database (TAHOD), this study was carried out to find the best-performing definition of LTFU and examine the characteristics of HIV-infected patients from the Asia-Pacific who were LTFU from treatment and care.

2. Methods

Established in 2003, TAHOD is a collaborative observational cohort study involving 18 sites in the Asia-Pacific region (see Acknowledgement). Detailed methods have been published previously [17]. Briefly, each site recruited approximately 200–300 HIV-infected patients, with recruitment based on a consecutive series of patients regularly attending a given site from a particular start-up time. Ethical approval for the study was obtained from the University of New South Wales Ethics Committee, Western Institutional Review Board, and respective local ethics committee from each TAHOD participating site.

The following data were collected: patient demographics and baseline data, CD4 and CD8 count, HIV viral load, prior and new AIDS defining illness (ADI), date and cause of death, prior and current prescribed antiretroviral treatment (ART), and reason for treatment change. Data were collected according to a common protocol. Upon recruitment, all available data prior to entry to TAHOD (considered as retrospective data) were extracted from patient case notes. Prospective data were updated six-monthly at each clinic and transferred to the data management centre for aggregation and analyses in March and September each year. TAHOD sites were encouraged to contact patients who have not been seen in the clinics in the previous 12 months.

TAHOD data submitted at March 2009 and March 2010 were used to find the best-performing definition of LTFU. TAHOD patients who had no followup after recruitment were not included in this analysis. Patients who were not seen in clinic for more than 12 months prior to the March 2010 data submission (i.e., last clinic visit prior to March 2009) were considered to be truly LTFU. The days between the last clinical visit and 31 March 2009 in the March 2009 data transfer were then used to find the interval that best classified a true LTFU in the following way. A series of cutoffs were considered, from ten to 365 days, to define patients as potentially LTFU. Each of these definitions of potential LTFU was compared with the gold standard of true LTFU, defined as no patient followup in the 12 months prior to 31 March 2010. The sensitivity and specificity of each cutoff in identifying true LTFU were calculated, and the best performing cutoff identified using the area under the receiver operator characteristic (ROC) curve. The optimal definition of LTFU identified in terms of maximising the sensitivity and specificity of true LTFU was found to be 180 days (see Results). This definition was then used in the risk factor analyses that follow.

Followup started from the last clinic visit at the March 2007 data submission. Patients who were considered LTFU before March 2007 (i.e., had no clinic visits 180 days before 31 March 2007) were excluded from the analysis. For patients enrolled after March 2007, the followup started at the time of enrolment. In terms of calculating person-years of followup, the end of followup for patients who had no clinic visit for 180 days and so were considered as LTFU was defined as 90 days after their last clinic visit. For patients not considered LTFU, the end of followup was also defined as 90 days after their last clinic visit. If a patient died, the followup was censored on the date of death if the date was within 180 days of their last clinic visit. Patients who died after March 2007 were considered to have complete followup. It should be noted that patients who were considered LTFU could return to clinic and reenter followup. The start of this reentry to followup was defined as 3 months prior to the first clinic visit that reinitiated followup. The patients that reentered followup could also be re-LTFU if the patient subsequently did not attend clinic for more than 180 days. The definitions we adopted were consistent with those in a previous study [18].

The rates of LTFU were calculated by the number of total LTFU periods divided by the total duration of followup contributed by the patients included in the analysis [18]. Because of the reentering and re-LTFU, patients could contribute more than one episode of LTFU in this analysis. The rates were further calculated in different strata, including age, sex, exposure category, hepatitis B and C infection, year since HIV infection, calendar year, the latest CD4 count and viral load, antiretroviral treatment status, CDC disease stages, prophylaxis (coded as receiving or not), and haemoglobin level, all taken at the start of each episode.

Factors associated with LTFU were assessed by multivariate Poisson regression models, using generalised estimating equations, to allow for multiple events of LTFU in the same patients. CD4 count, HIV viral load, antiretroviral treatment, AIDS diagnosis, and haemoglobin tests were included as time-dependent variables and updated at the time the new measurement or diagnosis was available.

Patients who had at least one episode of LTFU were then categorised into two groups: those who had no more clinical visits in the database (permanently LTFU) and those who later reentered followup (temporary LTFU). Multivariate logistic regression models were used to compare the characteristics in patients who were considered permanently LTFU with those who were temporary LTFU. All covariates were taken at the end of the episode in patients with truly LTFU or at the end of the first episode in patients considered temporary LTFU.

Multivariate models were built using a forward-stepwise approach. The final model included covariates that remained significant at the P < 0.05 level. Nonsignificant variables were also presented and adjusted for the final multivariate models. Data management and statistical analyses were performed using SAS for Windows (SAS Institute Inc., Cary, NC, USA) and Stata (StataCorp, STATA 10.1 for Windows, College Station, TX, USA).

3. Results

In March 2007, there were 2565 patients in the database. 1061 patients were subsequently enrolled in TAHOD up to March 2010. A total of 3626 patients from TAHOD who had follow-up visits in the clinic were included in this analysis. During the study period (from March 2007 to March 2010), there were 54 patients who died and considered to have complete followup.

Using days between last clinic visit and 31 March 2009 in the March 2009 data transfer, we identified the interval that best classifies a true LTFU (i.e., no clinic visit after 31 March 2009). An interval of 180 days was determined as the best-performing definition (Table 1, sensitivity 90.6%, specificity 92.3%). Using 180 days as the LTFU cutoff, during 7697 person-years of followup, a total of 1648 episodes of LTFU from 1298 patients were identified, giving a crude LTFU rate of 21.4 per 100 person-years (95% confidence interval, CI, 20.4 to 22.5). Of those 1648 episodes of LTFU identified using 180 days as the cutoff, 48% were considered permanently LTFU (i.e., the patient did not return to clinic before 31 March 2010), corresponding to 45% of the 1298 patients.

Table 1.

Receiver operating characteristic (ROC) analysis for the best-performing definition for loss to followup.

Cutoff (days) Sensitivity (%) Specificity (%) Area under ROC Cutoff (days) Sensitivity (%) Specificity (%) Area under ROC
10 99.67 16.97 58.32 160 90.96 90.77 90.87
20 99.02 24.32 61.67 170 90.64 91.44 91.04
30 98.05 31.31 64.68 175 90.64 92.05 91.34
40 96.82 39.90 68.36 180 90.55 92.26 91.41
50 96.34 49.52 72.93 185 90.23 92.53 91.38
60 95.77 57.20 76.48 190 89.33 93.01 91.17
70 95.28 65.52 80.40 200 88.52 93.44 90.98
80 95.11 71.26 83.19 210 87.79 94.13 90.96
90 94.71 77.62 86.16 240 85.26 95.25 90.26
100 94.22 80.91 87.57 270 83.55 96.43 89.99
120 93.24 86.18 89.71 300 82.00 97.04 89.52
150 91.53 90.17 90.85 365 78.99 97.73 88.36

True LTFU defined as no patient followup in the 12 month prior to 31 March 2010. Each cutoff used as a potential definition of LTFU was the days between last clinical visit and 31 March 2009 in the March 2009 data transfer. The sensitivity and specificity of each cutoff in identifying true LTFU were calculated, and the optimal cutoff identified based on ROC analysis.

The patient characteristics are summarised in Table 2. The majority of patients were male (71%), aged between 36 and 45 years (40%), and reported heterosexual transmission (64%). Chinese (27%), Thai (26%), and Indian (11%) were the main ethnic groups. At recruitment, approximately 12% did not have a CD4 count test, and of those tested, the majority had a CD4 count more than 200 cells/μL. Nearly half (45%) did not have an HIV viral load test, and of those tested, the majority were below 500 copies/mL. Close to half of the patients (46%) were diagnosed with an AIDS defining illness at recruitment, with tuberculosis being the main illness. Most patients (63%) had been reported to be diagnosed with HIV for less than 6 years when recruited to TAHOD (measured as the time from first reported positive HIV test). Less than 10% of the patients were coinfected with either hepatitis B or hepatitis C. At recruitment, the majority of patients had normal haemoglobin level. At the start of study followup, most of the patients were on antiretroviral therapy including three or more drugs in combination including at least one nucleoside reverse transcriptase inhibitor (NRTI) and one nonnucleoside reverse transcriptase inhibitor. Over 20% of patients were in a combination with at least one NRTI and a protease inhibitor (PI). All patients were receiving, or started, antiretroviral therapy during followup.

Table 2.

Patient characteristics.

Total 3626
Characteristics Number %
Sex
 Male 2567 71
 Female 1059 29

Current age (years)
≤35 1383 38
36–45 1449 40
46+ 794 22

Reported exposure
 Heterosexual contact 2337 64
 Homosexual contact 749 21
 Injecting drug use 263 7
 Other/unknown 277 8

Ethnicity
 Chinese 989 27
 Indian 390 11
 Thai 933 26
 Other/unknown 1314 36

Baseline CD4 count (cells/μl.)
 ≤100 239 7
 101–200 406 11
 201+ 2531 70
 Missing 450 12

Baseline HIV RNA (copies/ml)
 ≤500 1482 41
 501+ 379 10
 Missing 1765 49

CDC disease stage at baseline
 Stage A 1621 45
 Stage B 321 9
 Stage C 1684 46

Tuberculosis diagnosis at baseline
 No 2758 76
 Yes 868 24

Time since HIV infection (years)
 ≤5 2295 63
 6+ 1246 34
 Missing 85 2

Hepatitis B infection
 No 2297 63
 Yes 257 7
 Not tested 1072 30

Hepatitis C infection
 No 2007 55
 Yes 324 9
 Not tested 1295 36

Anemia at baseline
 No 2480 68
 Yes 597 16
Haemoglobin not tested 567 16
Antiretroviral treatment at baseline
 3 + (NRTI + NNRTI) 2224 61
 3 + (NRTI + PI) 744 21
 No/mono/double drug 583 16
 3 + (other combination) 75 2

Anemia: haemoglobin <13 g/dl (male), <11 g/dl (female); NRTI: nucleoside reverse transcriptase inhibitor; NNRTI: nonnucleoside reverse transcriptase inhibitor; PI: protease inhibitor.

Table 3 summarises univariate and multivariate analyses of factors associated with LTFU using 180 days as cut-off. In univariate analyses, the rate of LTFU was significantly lower in patients with a current CD4 counts above 200 cells/μL compared to patients with a CD4 count less than 100 cells/μL, but this was not significant in the final multivariate model. In the final multivariate model (Table 3), factors associated with LTFU included age (younger patients had higher rate of LTFU), current HIV viral load (either patients with HIV viral load ≥500 copies/mL or no tests in recent 180 days had higher rate of LTFU), history of HIV infection (patients with shorter history of HIV infection had higher rate of LTFU), hepatitis C infection (patients with positive hepatitis C antibody had higher rate of LTFU), and, finally, current combination of antiretroviral treatment (compared to patients on triple-drug regimen with at least one NRTI and one NNRTI, patients receiving no-, single-, or double-drug antiretroviral therapy, or a triple-drug regimen containing at least one NRTI and one PI, had higher rate of LTFU).

Table 3.

Factors associated with permanent or temporary LTFU, defined as no clinic visit for 180 days, among all patients under followup.

Person- years Number LTFU Crude Rate1 Adjusted
95% CI IRR2 95% CI P value IRR2 95% CI P value
Sex
 Male 5468.1 1206 22.06 (20.85, 23.34) 1.00 1.00
 Female 2229.2 442 19.83 (18.06, 21.77) 1.10 (0.98, 1.24) 0.090 1.04 (0.93, 1.17) 0.446

Current age (years)
 ≤35 2210.4 575 26.01 (23.97, 28.23) 1.00 1.00 0.0023
 3645 3320.2 718 21.62 (20.10, 23.27) 0.82 (0.74, 0.92) 0.001 0.89 (0.79, 1.00) 0.050
 46+ 2166.6 355 16.39 (14.77, 18.18) 0.69 (0.60, 0.79) <0.001 0.76 (0.66, 0.88) <0.001

Reported exposure
 Heterosexual  contact 5144.5 985 19.15 (17.99, 20.38) 1.00 1.00
 Homosexual  contact 1707.2 344 20.15 (18.13, 22.40) 1.10 (0.93, 1.29) 0.275 1.05 (0.89, 1.25) 0.540
 Injecting drug use 344.3 125 36.31 (30.47, 43.27) 1.21 (0.97, 1.51) 0.098 1.10 (0.86, 1.40) 0.437
 Other/unknown 501.3 194 38.70 (33.62,44.55) 1.64 (1.37, 1.98) <0.001 1.56 (1.29, 1.88) <0.001

Current CD4 count (cells/μl.)
 ≤100 233.7 69 29.52 (23.32, 37.38) 1.00 1.00
 101–200 635.7 136 21.40 (18.09, 25.31) 0.92 (0.68, 1.22) 0.551 0.96 (0.72, 1.29) 0.800
 201+ 6327.6 1181 18.66 (17.63, 19.76) 0.75 (0.58, 0.96) 0.023 0.79 (0.61, 1.02) 0.071
 Missing 500.3 262 52.37 (46.40, 59.11) 1.18 (0.90, 1.55) 0.235 0.99 (0.74, 1.31) 0.922

Current HIV RNA (copies/ml)
 ≤500 4213.7 679 16.11 (14.95, 17.37) 1.00 1.00 0.0213
 501+ 537.1 158 29.42 (25.17, 34.38) 1.71 (1.43, 2.04) <0.001 1.24 (1.03, 1.51) 0.026
 Missing 2946.4 811 27.52 (25.69, 29.49) 1.75 (1.55, 1.98) <0.001 1.64 (1.45, 1.86) <0.001

CDC disease stage
 Stage A 3205.1 828 25.83 (24.13, 27.65) 1.00 1.00
 Stage B 801.6 118 14.72 (12.29, 17.63) 0.93 (0.76, 1.14) 0.507 0.95 (0.77, 1.17) 0.623
 Stage C 3690.5 702 19.02 (17.67, 20.48) 0.84 (0.75, 0.93) 0.001 0.92 (0.82, 1.02) 0.125

Tuberculosis diagnosis
 Yes 1806.7 372 20.59 (18.60, 22.79) 1.00 1.00
 No 5890.6 1276 21.66 (20.51, 22.88) 1.04 (0.92, 1.18) 0.537 0.98 (0.87, 1.12) 0.801

Time since HIV infection (years)
 ≤5 3477.2 785 22.58 (21.05, 24.21) 1.00 1.00 0.0053
 6+ 4115.7 844 20.51 (19.17, 21.94) 0.84 (0.75, 0.94) 0.002 0.89 (0.79, 1.00) 0.048
 Missing 104.3 19 18.21 (11.61, 28.55) 0.58 (0.36, 0.94) 0.027 0.49 (0.30, 0.79) 0.004

Hepatitis B infection
 Yes 584.5 112 19.16 (15.92, 23.06) 1.00 1.00
 No 5101.9 883 17.31 (16.20, 18.49) 0.93 (0.76, 1.13) 0.474 0.90 (0.74, 1.10) 0.319
 N/A 2010.8 653 32.48 (30.08, 35.06) 0.98 (0.80, 1.21) 0.859 1.07 (0.85, 1.35) 0.548

Hepatitis C infection
 Yes 541.4 149 27.52 (23.44, 32.31) 1.00 1.00 0.0303
 No 4692.8 796 16.96 (15.82, 18.18) 0.81 (0.67, 0.98) 0.029 0.81 (0.67, 0.98) 0.034
 N/A 2463.0 703 28.54 (26.51, 30.73) 0.75 (0.62, 0.91) 0.004 0.77 (0.63, 0.93) 0.008
Current anemia (male < 13 g/dl, female < 11 g/dl)
 Yes 1021.1 155 15.18 (12.97, 17.77) 1.00 1.00
 No 5771.6 1157 20.05 (18.92, 21.24) 1.09 (0.92, 1.30) 0.302 1.11 (0.94, 1.32) 0.227
 N/A 904.5 336 37.15 (33.38, 41.34) 1.31 (1.07, 1.59) 0.008 1.09 (0.89, 1.34) 0.382
Current ART4
 3 + (NRTNRTI) 4830.8 942 19.50 (18.29, 20.79) 1.00 1.00 0.0013
 3 + (NRTI + PI) 1898.3 377 19.86 (17.95, 21.97) 1.21 (1.06, 1.38) 0.005 1.22 (1.07, 1.39) 0.003
 No/mono/double ARV 762.7 300 39.33 (35.12, 44.05) 2.18 (1.90,2.50) <0.001 1.92 (1.66, 2.22) <0.001
 3 + (other combination) 205.4 29 14.12 (9.81, 20.32) 0.95 (0.65, 1.38) 0.786 1.01 (0.69, 1.47) 0.975

(1) Crude rate, per 100 person-years.

(2) Stratified by TAHOD sites.

(3) Overall for test for trend (ordinal categorical covariates) or for homogeneity (nominal categorical covariates).

(4) ART: NRTI: nucleoside reverse transcriptase inhibitor; NNRTI: nonnucleoside reverse transcriptase inhibitor; PI: protease inhibitor.

Table 4 shows factors that predict permanent LTFU among patients who had no clinic visit for 180 days and so met our optimal definition of LTFU. In the final multivariate model, patients permanently LTFU were more likely to be older, have not been anemic, have no recent HIV viral load test, have tested negative for hepatitis C infection or have never tested for hepatitis C, and have had more than one episode of previous temporary LTFU.

Table 4.

Factors that predict permanent LTFU in patients without a clinic visit for 180 days.

Number True loss % OR1 95% CI P value Adjusted OR1 95% CI P value
Sex
 Male 1206 584 48.4 1.00 1.00
 Female 442 209 47.3 0.89 (0.69, 1.15) 0.359 0.80 (0.61, 1.05) 0.104

Current age (years)
 ≤35 568 278 48.9 1.00 1.00 0.0972
 3645 717 340 47.4 1.33 (1.03, 1.71) 0.031 1.31 (1.00, 1.72) 0.050
 46+ 363 175 48.2 1.27 (0.94, 1.72) 0.118 1.28 (0.93, 1.77) 0.128

Reported exposure
 Heterosexual contact 985 443 45.0 1.00 1.00
 Homosexual contact 344 199 57.8 1.12 (0.78, 1.60) 0.532 1.24 (0.85,1.81) 0.262
 Injecting drug use 125 55 44.0 1.01 (0.59, 1.73) 0.969 1.32 (0.72, 2.41) 0.364
 Other/unknown 194 96 49.5 1.07 (0.69, 1.64) 0.773 1.22 (0.78, 1.93) 0.382

Current CD4 count (cells/μl.)
 ≤100 58 36 62.1 1.00 1.00
 101–200 129 66 51.2 0.76 (0.36, 1.60) 0.471 0.99 (0.47, 2.13) 0.989
 201+ 1068 465 43.5 0.62 (0.33, 1.18) 0.144 0.82 (0.42, 1.59) 0.551
 Missing 393 226 57.5 1.50 (0.77, 2.93) 0.238 1.18 (0.58, 2.42) 0.649

Current HIV RNA (copies/mL)
 ≤500 598 230 38.5 1.00 1.00 0.0112
 501+ 153 78 51.0 1.02 (0.68, 1.52) 0.924 0.94 (0.62, 1.42) 0.767
 Missing 897 485 54.1 2.13 (1.63, 2.80) <0.001 1.54 (1.13, 2.09) 0.006

CDC disease stage
 Stage A 828 413 49.9 1.00 1.00
 Stage B 121 54 44.6 0.77 (0.48, 1.22) 0.258 0.70 (0.43, 1.14) 0.154
 Stage C 699 326 46.6 1.00 (0.78, 1.27) 0.975 1.05 (0.81, 1.36) 0.702

Tuberculosis diagnosis
 Yes 361 186 51.5 1.00 1.00
 No 1287 607 47.2 0.87 (0.66, 1.16) 0.342 0.85 (0.63, 1.15) 0.297

Time since HIV infection (years)
 ≤5 771 400 51.9 1.00 1.00
 6+ 858 389 45.3 1.25 (0.98, 1.60) 0.076 1.03 (0.79, 1.34) 0.835
 Missing 19 4 21.1 0.37 (0.12, 1.17) 0.091 0.43 (0.13, 1.43) 0.170

Hepatitis B infection
 Yes 112 47 42.0 1.00 1.00
 No 883 431 48.8 1.30 (0.84, 2.03) 0.243 1.35 (0.84, 2.16) 0.222
 N/A 653 315 48.2 1.31 (0.82, 2.09) 0.253 1.03 (0.60,1.76) 0.908
Hepatitis C infection
 Yes 149 66 44.3 1.00 1.00 0.0042
 No 796 376 47.2 1.57 (1.01, 2.45) 0.046 1.66 (1.04, 2.66) 0.034
 N/A 703 351 49.9 1.96 (1.26, 3.05) 0.003 2.16 (1.35, 3.46) 0.001

Current anemia (male < 13 g/dL, female < 11 g/dL)
 Yes 141 87 61.7 1.00 1.00 <0.0012
 No 1065 456 42.8 0.53 (0.35, 0.81) 0.003 0.50 (0.32, 0.76) 0.001
 N/A 442 250 56.6 1.15 (0.73, 1.81) 0.549 0.78 (0.49, 1.26) 0.310

Current ART**
 3 + (NRTI + NNRTI) 911 404 44.3 1.00 1.00
 3 + (NRTI + PI) 356 167 46.9 0.76 (0.57, 1.02) 0.072 0.74 (0.54,1.01) 0.057
 No/mono/double ARV 352 209 59.4 0.93 (0.69, 1.26) 0.644 0.78 (0.57, 1.08) 0.137
 3 + (other combination) 29 13 44.8 0.89 (0.40, 1.98) 0.770 0.85 (0.38, 1.94) 0.707
Previous episode of temporary LTFU
 None 1298 589 45.4 1.00 1.00 <0.0012
 Once 296 158 53.4 2.79 (2.05, 3.80) <0.001 2.71 (1.97, 3.72) <0.001
 Twice 54 46 85.2 31.76 (13.91, 72.52) <0.001 27.75 (12.03, 64.01) <0.001

(1) Stratified by TAHOD sites.

(2) Overall for test for trend (ordinal categorical covariates) or for homogeneity (nominal categorical covariates).

(3) ART: NRTI: nucleoside reverse transcriptase inhibitor; NNRTI: nonnucleoside reverse transcriptase inhibitor; PI: protease inhibitor.

4. Discussion

We found that an interval of 180 days between clinic visits was the best-performing definition of LTFU based on sensitivity and specificity in identifying true LTFU. By this definition, we observed that approximately one in five patients in our cohort would miss clinic visits for more than 180 days and so become defined as LTFU. Among these patients in our cohort close to half eventually returned to followup, with half becoming truly lost to HIV-related treatment and care.

The 180-day cutoff has been used by other studies as a working definition of LTFU [10, 1921]. Other intervals have also been proposed as measurements of classifications of LTFU, such as 90 days [8] and 365 days [9]. Regional- and cohort-dependent characteristics, such as scheduled clinic visits, patient burden, and drug availability could result in specific intervals that best categorise patients at risk of LTFU. Nevertheless, a 180-day (or 6-month) cutoff is an appealing and easy-to-apply definition that could be used in different clinical settings in the Asia-Pacific region to flag patients at risk of being permanently lost to treatment and care. Our analyses suggest patients with no clinic visits for six months are at high risk of being permanently lost and should be aggressively traced.

Chi et al. also found that a cutoff of 180 days was optimal to define LTFU after analysing data from the Africa, Asia, and Latin America regions of the IeDEA collaboration (including data from our cohort) [22]. There are some methodological differences between our analyses, principally regarding minimum numbers of patients for site inclusion. Chi et al. found quite extensive heterogeneity between sites, something we also found to a lesser extent. However, it is nevertheless reassuring that we found a similar optimal cutoff of 180 days without clinic visits to define LTFU. With rapid scaling up of antiretroviral treatment taking place globally, there is a need to adopt a universal consistent definition of LTFU, or a general algorithm to define cutoffs, to evaluate HIV treatment programs in different regions [6, 7, 19].

Over one in five patients in our cohort failed to come to clinic for more than 180 days in a given year. Similar rates have also been found in patients from Africa [3, 11]. However, the LTFU rate was lower in EuroSIDA [23], a large prospective cohort study with HIV-infected patients mainly from Europe (using one year as a cutoff). Approximately half of the patients who experienced LTFU in our study later came back to clinic, and patients who had a previous episode of LTFU were more likely to prove to be true LTFU, similar to previous findings [18].

We found that younger patients, patients infected with hepatitis C, and patients with detectable or unmeasured viral load were more likely to experience LTFU. These findings are all consistent with previous study findings [10, 11, 2426]. Patients with undetectable viral load are likely to be motivated and adherent to antiretroviral treatment and thus remain in care. Among those patients who experienced LTFU, we found that those who tested negative for hepatitis C infection or were never tested for hepatitis C were more likely to be permanently LTFU. This finding seems counterintuitive, but it might be that patients who have tested positive for hepatitis C receive more medical attention from their clinicians and thus prove less likely to be permanently LTFU. Among patients identified as LTFU, anemic patients were also more likely to be permanently lost to treatment and care. Anemia has been shown to be a strong prognostic marker for HIV disease progression and survival [27], which could, at least in part, explain these patients failing to return to followup.

Compared to patients on NNRTI-based regimen, patients receiving no-, single-, or double-drug antiretroviral therapy or a triple-drug regimen containing PI were more likely to experience LTFU. The reasons for this are not clear. The greater loss to followup may be associated with increased drug toxicity, either resulting in a patient receiving mono- or dual therapy or from receiving a PI. Patients receiving PI-based regimens are also those who are more likely to be on a second line regimen, a regimen that may be substantially more expensive than first line. In the Asia Pacific region, out-of-pocket expenses are needed to pay for treatment in some clinics. Hence, the lost to followup may be associated with drug availability or affordability. It is worth noting that patients receiving mono- or dual therapy, or a PI based regimen, were also associated with being less likely to be permanently lost to followup, that is to say more likely to return to clinic (albeit not quite statistically significantly so). This possibly supports the idea of these regimens being associated with short-term drug availability or affordability issues. Unfortunately, data are not available to address this issue in any greater detail.

It has been shown that, in resource-limited settings, predominantly in Africa, patients who are LTFU have a much poorer prognosis than patients who remain in followup [5]. In part, this is due to a proportion of patients who die not having vital status information updated at their treatment site. The extent to which this occurs in TAHOD is uncertain. While it seems likely that at least some patients who are LTFU have died without this information reaching the site, the lack of association between key measures of HIV disease progression, such as CD4 count and AIDS defining illnesses, and LFTU suggests it may be lower than in African settings. However, this association between LTFU and poorer prognosis underpins the need for consistent definitions of LTFU in research cohort studies, and where there are possible active patient tracing strategies or at least sampling-based approaches [28] to ensure comparability of results across studies and settings.

Several limitations should be considered in interpreting the results in this paper. First, TAHOD participating sites are generally urban referral centres, and the patients recruited in TAHOD were those regularly attending a given TAHOD site. Hence, TAHOD patients are not representative of all HIV-infected patients in the Asia and Pacific region. The overall rate of LTFU we saw in our study is therefore likely to be an underestimate of rates across the region. However, the effect of these sampling biases on the optimal definition of LTFU and on the covariate analyses is arguably less strong. It is reassuring that our estimate of the optimal definition of LTFU is consistent with that seen across Africa and Latin America [22]. Second, since antiretroviral treatment has become more decentralised and available in distant or rural communities with rapid scale-up programs, patients might choose to receive treatment and care locally rather than at tertiary and referral centres [29, 30]. Consequently, patients may have been retained in care but not necessarily in the clinics involved in this study. Information on referral to other health facility was only recently included in the data collection, so we could not further verify if patients were retained in care or truly loss to health services. Third, we do not collect data on the measures TAHOD sites undertake to routinely trace patients who are LTFU. These measures differ across sites according to local practices and conditions. Effective patient tracking and recording are essential to program evaluation and maintenance of treatment and care [1, 18]. What patient tracking measures are effective in retaining patients in treatment and care in the Asia-Pacific region is an area that deserves further research. We also do not have data on transportation [31], social and economic status [32], pregnancy for women [10], and community support [33], all of which have been found to be important determinants of LTFU. Lastly, the patients included in this study were all receiving, or started, antiretroviral treatment and had clinical assessments. Consequently, the results cannot be extrapolated to patients not yet initiated on antiretroviral therapy. Research into followup among HIV-infected patients not receiving antiretroviral treatment in the Asia-Pacific region needs to be considered [3436], particularly in the context of the move to start treatment earlier.

5. Conclusion

With rapid scaleup of antiretroviral treatment, it is essential to study factors that predict loss to followup and identify patients at risk of loss to treatment and care, particularly in resource-limited settings. At the treatment and care level, this can maintain efficacy of antiretroviral therapy and avoid adverse events. At the program evaluation level, the impact of loss to followup on overall treatment outcome, disease progression, and survival can then be accounted for with appropriate statistical adjustments. Collaboration with HIV treatment programs in other regions in studies on LTFU and in particular standardisation of LTFU definitions are essential for reporting and program evaluation.

Acknowledgments

The TREAT Asia HIV Observational Database and the Australian HIV Observational Database are part of the Asia Pacific HIV Observational Database and are initiatives of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the following institutes of the US National Institutes of Health (NIH): National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Child Health and Human Development (NICHD), the Office of the Director (OD), and the National Cancer Institute (NCI), as part of the International Epidemiologic Databases to Evaluate AIDS (IeDEA) (Grant no. U01AI069907). Additional support is provided by the Dutch Ministry of Foreign Affairs through a partnership with Stichting Aids Fonds and from the Austrian AIDS Life Association (AALA). The National Centre in HIV Epidemiology and Clinical Research is funded by the Australian Government Department of Health and Ageing and is affiliated with the Faculty of Medicine, The University of New South Wales. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions mentioned above.

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