Baseline and Sociodemographic Characteristics
In this retrospective follow up study, a total of 485 patient cards were retrieved and analyzed. The median age of participants was 33 years (Q1, Q3: 27,40). Two hundred seventy-three (44.7%) of the study participants were outside of the catchment area and 59.8% were females (Table 1).
Table 1: Baseline and Socio-demographic characteristics of patients on ART, Debre Markos Referral Hospital, 2008 -2018.
Characteristics
| | Frequency
| Percentage
|
Age in years
| 15-24
| 63
| 13.0
|
| 25-34
| 203
| 41.9
|
| 35-44
| 146
| 30.1
|
| >=45
| 73
| 15.1
|
Marital status
| Not married
| 82
| 16.9
|
| Married
| 224
| 46.2
|
| Divorced
| 117
| 24.1
|
| Widowed
| 62
| 12.8
|
Occupation
| Sex workers
| 15
| 3.1
|
| Drivers
| 22
| 4.5
|
| Contract employee(private)
| 312
| 64.3
|
| Farmer
| 52
| 10.7
|
| Government employee
| 79
| 16.3
|
| Others*
| 5
| 1.0
|
Religion
| Orthodox
| 432
| 89.1
|
| Muslim
| 45
| 9.3
|
| Other**
| 8
| 1.6
|
Education
| No formal education
| 151
| 31.1
|
| Primary education
| 132
| 27.2
|
| Secondary education
| 202
| 41.6
|
BMI
| Under weight
| 167
| 34.4
|
| Normal
| 293
| 60.4
|
| Overweight and obese
| 25
| 5.2
|
CD4 count
| CD4 <=200
| 291
| 60.0
|
| CD4 >200
| 194
| 40.0
|
Baseline regimen
| 1a=d4t-3TC-NVP
| 76
| 15.7
|
| 1b=d4t-3TC-EFV
| 68
| 14.0
|
| 1c=AZT-3TC-NVP
| 76
| 15.7
|
| 1d=AZT-3TC-EFV
| 42
| 8.7
|
| 1e=TDF-3TC-EFV
| 208
| 42.9
|
| 1f=TDF+3TC+NVP
| 7
| 1.4
|
| 1g=ABC+3TC+EFV
| 7
| 1.4
|
| 1h=ABC+3TC+NVP
| 1
| 0.2
|
*Students, unemployed ** protestant, catholic
Incidence Rates of Adverse Drug Reactions
Out of the total 485 participants 67 (13.81%; 95% C.I: 10.7%, 16.8%) had experienced sever adverse drug reactions (ADRs).
Of the total 67 observed events anemia account for the majority 28 (41.79%) of ADRs, followed by peripheral neuropathy 19(28.36%) and serious skin reactions 9(13.43%). The remaining forms of ADRs were lipodystrophy 4(5.97%), vomiting 4(5.97%), renal failure 2(2.98%) and hepatotoxicity 1(1.49%).
The incidence rate of ADR development was 3 (95% C.I: 2.4, 3.86) per 100-person years, with a total of 2202.7 follow up years. The incidence rates in male and female were 19.3 and 38.5 per 1000-person years of follow up respectively. In the other hand, the incidence rate of ADR was lower among those who took cotrimoxazole preventive therapy compared to their counterparts (27.8/1000 PY and 40.5/1000PY) respectively. The incidence rate varies at different interval of the cohort (Table 2)
The overall cohort, censoring and event median follow up times were 51 (Q1, Q3: 17, 90), 56 (Q1, Q3: 14.75, 96.25) and 47 (Q1, Q3: 31,56) months respectively. Due to the smaller proportion of the event in the cohort, the median survival time was not estimable. So, we used the survival mean to estimate the mean survival time. In this regard, the survival mean will be estimated better considering the maximum event time, which is reported as restricted mean survival time [13]. The estimated mean survival time using the restricted mean was 73.72 (95% C.I: 71.84, 75.60) months. In the other hand, the estimated median survival time among those experienced the event of interest (ADR) was 47 (95% C.I: 40.8, 53) months.
Majority of the ADRs were encountered among those whose baseline ART regimen was d4T-3TC-NVP (43.3%) followed by d4T-3TC-EFV (37.3%). The proportion was also high among those with baseline WHO stage of III and IV (28.4% and 43.3%) respectively.
Table 2: Person time follow up and incidence rates of ADR among patients on ART, Debre Markos Referral Hospital 2008 to 2018.
Cohort (years)
| person-time
| failures
| rate
| 95% Conf.
| Interval
|
(0 - 1]
| 435.25
| 10
| 0.02
| 0.012
| 0.042
|
(1 - 2]
| 364.42
| 4
| 0.01
| 0.004
| 0.029
|
(2 - 3]
| 329.25
| 10
| 0.03
| 0.016
| 0.056
|
(3 - 4]
| 281.58
| 14
| 0.05
| 0.029
| 0.083
|
(4 - 5]
| 230.92
| 24
| 0.10
| 0.069
| 0.155
|
> 5
| 561.25
| 5
| 0.01
| 0.004
| 0.021
|
Survival probability
Majority (92.5%) of the ADRs occurred up to the end of 5th year of follow up, with more than half the events encountered in the interval between three and five years (Table 3).
Table 3: Cumulative survival probability at different time intervals among patients on ART, Debre Markos Referral Hospital, 2008 -2018.
Time (year)
| Beginning Total
| Fail
| Cumulative Survival
| 95% C. I
|
1
| 393
| 10
| 0.98
| (0.96, 0.99)
|
3
| 306
| 14
| 0.94
| (0.91, 0.96)
|
5
| 201
| 38
| 0.80
| (0.75, 0.84)
|
7
| 145
| 5
| 0.78
| (0.73, 0.82)
|
10
| 6
| 0
| 0.78
| (0.73, 0.82)
|
Figure 1: Cumulative survival Kaplan Meier curve for time to the development of ADRs among HIV patients on ART, Debre Markos Referral Hospital.
Factors Associated with Time to the Development of ADRs in Bivariable Analysis
Variables with p-values of less than 0.25 from univariable analysis were screened for multivariable analysis in Cox proportional hazard model. Variables including gender, residence, baseline WHO stage, occupation, baseline regimen, regimen change, baseline CD4 cell count, taking cotrimoxazole preventive therapy, baseline BMI, experience of TB infection and baseline functional status candidate for multivariable analysis. Some of the variables also were significant at p – value of 0.05.
Female were less survivors to develop ADR than males (Figure 3)
Figure 2: Kaplan Meier curves for time to the development of ADRs among HIV patients on ART by gender, Debre Markos Referral Hospital 2008 to 2018.
Those from outside of the catchment area to Debre Markos referral hospital were at lower survival compared to those living within the catchment area.
Figure 3: Kaplan Meier curves for time to the development of ADRs among HIV patients on ART by source of residence, Debre Markos Referral Hospital 2008 to 2018.
Goodness of Fit of the Final Model
The goodness of fit of the final Cox regression model was evaluated using the estimate of Cox-Snell residuals drawn against the Nelson-Aalen cumulative hazard function (Figure 5).
Figure 4:Goodness of fit of the final Cox proportional hazards regression model using Cox Snell Residuals
The hazard function follows the forty-five-degree line very closely except for large values of time. It is very common for models with censored data to have some wiggling at large values of time and it is not something which should cause much concern [14]. Therefore, we would conclude that the final model fits the data well.
Predictors of Time to Development of Severe ADRS among Patients on ART
After checking for the Cox proportional hazard assumptions using the graphical, statistical and time dependent methods, the multivariable Cox proportional model was run.
Those with livelihood of commercial sex work and car driving were 2.78 times at higher risk of developing ADR compared to those with contract employment (95% C.I: 1.31, 5.92). Patients residing out of the catchment area to the facility were 73% at higher risk to develop ADR at any time, compared to those living within the catchment area (AHR=1.73; 95% C.I: 1.04, 2.86). The risk of ADRs among patients with baseline WHO clinical stage of III and IV was 2.59 times higher at any time compared to those with WHO stages I and II (95% C.I: 1.54, 4.36).
Patients who ever took anti-TB prophylaxis were 2.83 times more likely to develop adverse drug reactions at any time in the follow up compared to those with no such experience (95% C.I: 1.61, 4.96). In the other hand, patients who were on ART regimen groups d4t-3TC-NVP and d4t-3TC-EFV at baseline and those who experienced regimen change from their baseline for reasons other than ADR were at higher risk of developing ADRs (Table 4).
Table 4: Cox regression analysis of the relationship between explanatory variables and the time to ADR development, Debre Markos Referral Hospital, 2008 – 2018.
| Survival Status
|
|
|
Variables
| Event (ARD)
| Censored
| CHR (95% C.I)
| AHR (95% C.I)
|
Gender
|
|
|
|
|
Male
| 18
| 177
| 1.00
| 1.00
|
Female
| 49
| 241
| 2.01 (1.17, 3.46)
| 1.62 (0.91, 2.89)
|
Occupation
|
|
|
|
|
Contract Employee
| 33
| 272
| 1.00
| 1.00
|
Sex workers and drivers
| 10
| 27
| 2.14 (1.06, 4.35)
| 2.78 (1.31, 5.92) **
|
Merchant
| 5
| 4
| 5.77 (2.24, 14.81)
| 2.63 (0.81, 8.48)
|
Farmer
| 11
| 41
| 2.29 (1.16, 4.53)
| 2.51 (1.22, 5.16) *
|
Government Employee
| 8
| 74
| 0.75 (0.34, 1.62)
| 1.19 (0.53, 2.71)
|
Residence
|
|
|
|
|
Within catchment area
| 28
| 245
| 1.00
| 1.00
|
Out of catchment area
| 39
| 173
| 1.72 (1.06, 2.79)
| 1.73 (1.04, 2.86) *
|
Baseline WHO stage
|
|
|
|
|
Stage I and II
| 25
| 245
| 1.00
| 1.00
|
Stage III and IV
| 42
| 173
| 2.81 (1.71, 4.62)
| 2.59 (1.54, 4.36) ***
|
Baseline regimen
|
|
|
|
|
1c+1d+1e+1f
| 11
| 322
| 1.00
| 1.00
|
1a +1b
| 54
| 90
| 7.99 (4.18, 15.30)
| 4.03 (1.98, 8.20) ***
|
1g+1h
| 2
| 6
| 6.59 (1.46, 29.72)
| 4.57 (0.79, 26.34)
|
Baseline CD4
|
|
|
|
|
<=200
| 52
| 239
|
| 1.00
|
>200
| 15
| 179
| 0.62 (0.35, 1.09)
| 1.10 (0.60, 2.05)
|
Regimen changed
|
|
|
|
|
Yes
| 62
| 125
| 16.63 (6.68, 41.37)
| 9.99 (3.79, 26.28) ***
|
No
| 5
| 293
| 1.00
| 1.00
|
Ever took CPT
|
|
|
|
|
Yes
| 49
| 323
| 1.00
| 1.00
|
No
| 18
| 95
| 1.49 (0.39, 1.15)
| 1.38 (0.79, 2.43)
|
Anti TB prophylaxis
|
|
|
|
|
Yes
| 43
| 286
| 1.32 (0.80, 2.18)
| 2.83(1.61, 4.96) ***
|
No
| 24
| 132
| 1.00
| 1.00
|
Functional status
|
|
|
|
|
Working
| 43
| 319
| 1.00
| 1.00
|
Ambulatory
| 20
| 86
| 1.35 (0.79, 2.3)
| 1.43 (0.77, 2.64)
|
Bed ridden
| 4
| 13
| 1.61 (0.58, 4.48)
| 1.38 (0.43, 4.45)
|
1a= d4t-3TC-NVP, 1b= d4t-3TC-EFV, 1c = AZT-3TC-NVP, 1d= AZT-3TC-EFV, 1e= TDF-3TC-EFV, 1f=TDF+3TC+NVP, 1g=ABC+3TC+EFV, 1h=ABC+3TC+NVP, CPT=cotrimoxazole preventive therapy, *** significant at p value of 0.001, ** significant at p value of 0.01, * significant at p value of 0.05