Contraceptive implant failures among women using antiretroviral therapy in western Kenya: a retrospective cohort study

Data collection

Between January 2016 and March 2017, eleven research assistants (RAs) reviewed medical charts of all women receiving care at Comprehensive Care Clinics (CCC) for PLHIV in nine public-sector facilities in five counties. RAs retrieved medical records for all female clients who were seen at the CCCs between January 2011 and December 2015 and verified whether they were of reproductive age, on ART, and using a contraceptive implant. Women who did not meet these criteria were excluded from further data abstraction. Data abstracted from women’s medical records included: date of birth, implant type, date inserted, date removed, reason for removal, date of enrollment into HIV care, age at enrollment into care, date of ART start, date of stopping ART, ART regimen (multiple entries possible for start, end dates and type of ART regimen), date of transfer or death, notations of pregnancy in records, CD4 count, viral load results and date taken, number of liver function tests done and results, WHO stage, height and weight (to calculate BMI), tuberculosis (TB) status, and other concurrent chronic conditions (hepatitis, diabetes, hypertension) with dates of diagnosis and other medications used. The study was reviewed and approved by the Johns Hopkins School of Public Health review board (#6073) and the Kenya Medical Research Institute scientific and ethical review committee (#NON-SSC 510).

In cases where RAs were unable to complete full data abstraction from the client’s CCC medical record, they consulted other hospital records, including case notes from the consulting health care provider, Family Planning Register, PMTCT Register, Antenatal Care (ANC) Register, Logistics Management Information System, and laboratory records. For several clients in four Kisumu County facilities, the study team retrieved information on implant type from Marie Stopes Kenya’s database of family planning outreach events.

The investigators sought to identify possible pregnancies due to contraceptive implant failures from medical records: specifically, records of the client’s reason for implant removal as pregnancy or that the client gave birth after receiving an implant and before its removal date.

Each CCC client receives a unique identifier (eleven-digit, alpha-numeric code) at enrollment in HIV care and treatment services. The investigators only used this number to locate client records for data verification purposes. Client names were tallied but not included in data abstraction. De-identified data were entered into REDCap v6.14.0 (Research Electronic Data Capture), a web-based data management application, with limited, password-protected access. RAs were strictly instructed to properly store all paper and electronic copies of records with client-identifying information. Portable electronic devices did not contain identifiable information.

Data cleaning

The investigators abstracted 1,612 records from women concurrently using ART and an implant. Investigators excluded all 208 records from Busia County Referral Hospital due to inconsistencies in RAs' adherence to standard operating procedures. Subsequently, investigators removed: 36 suspected duplicate records, 50 records with invalid ART or missing implant data, 81 records which indicated that there was fewer than three consecutive months of concurrent implant and ART use, and 85 records where the woman did not meet other inclusion criteria.

All observations without concurrence end dates were censored at December 31, 2015 or earlier if the end of approved implant effectiveness (3 years for Implanon/Nexplanon® and Levoplant® and 5 years for Jadelle®, per WHO prequalifications²⁵) preceded the end of the observation period. Records which listed emtricitabine (FTC) within the ART regimen were regrouped with 3TC due to pharmacokinetic similarity²⁶.

With exclusions, the dataset included 1,152 individual women (Table 1). The dataset was then expanded so that women who switched to a new ART and/or implant over the course of the study period were recoded as separate observations for each unique ART/implant co-administration, giving a final dataset of 1,190 observations.

Data analysis

We estimated contraception failure rates for LNG and ETG implants with concurrent ART regimens containing EFV, NVP, or a protease inhibitor (PI). We estimated the incidence of unintended pregnancy per 100-woman years at risk. We defined person years at risk as the start of concurrent implant and ART use (beginning from the start date of whichever was introduced second) to either pregnancy, date of implant removal, end of approved implant effectiveness, end of ART use, or end of the study period, whichever came first. Incidence of unintended pregnancy was calculated as number of pregnancies/number of woman-years at risk x100, assuming a constant rate of implant failure.

We used Poisson regression to calculate the incidence rate ratios (IRRs) of pregnancy by age, CD4 count, BMI, ART regimen, and implant type. We repeated this for all six possible combinations of concurrent ART and implant use. Data on TB symptom screening, TB diagnosis and viral load were missing for over 96% of women, precluding analysis of these variables. Differences were deemed statistically significant at the p<0.05 level (two-sided test of significance). IRRs were calculated after adjusting for potential clustering within HIV clinics, using cluster-adjusted standard errors^27,28. To test for robustness of results, we reran analyses excluding women aged 35–49. Two separate investigators conducted analyses and cross-checked results; both used STATA with slightly different versions (14 and 15).

Kaplan-Meier failure curves were created to visualize time-to-implant failure for the different ART and implant combinations by using the date of unintended pregnancy as the failure date. We present duration of concurrent ART-implant use for interpretation of Kaplan-Meier results.

Demographic and ART information

Table 2 provides age and clinical status of women during each instance of concurrent use of ART and an implant, which allows individuals who changed their regimen and/or implant during the study period to be counted as more than one observation. The most common combination of implant and ART use was LNG-EFV (39.4%), followed by ETG-EFV (26.7%), LNG-NVP (16.7%), ETG-NVP (14.8%), LNG-PI (1.3%), and ETG-PI (1.0%).

In total, 32 of the 1,152 women included in the dataset switched ART regimens while using an implant during the study period; 30 women were exposed to two regimens and two women were exposed to three regimens. Four women used implants twice. Three women were exposed to three different combinations of implant and ART.

Pregnancy incidence

Table 3 presents pregnancy IRRs and incidence in person-years of observations broken down by clinical status of women at each observation of co-administration. There were 115 pregnancies in the 1,190 instances of co-administration, yielding a pregnancy incidence rate of 6.32 (95% CI: 5.27–7.59), with 9.26 (95% CI: 7.18–11.96) among ETG and 4.74 (95% CI: 3.65–6.16) among LNG implant users, respectively.

Analysis of incidence by ART and contraceptive use

The pregnancy IRRs did not differ between EFV- and NVP-based regimens (IRR = 1.00; 95% CI: 0.71–1.43). No pregnancies were recorded among women on non-NNRTI-based regimens among both ETG and LNG implant users, which was statistically significant. There was also a statistically significant difference in pregnancy rates based on implant type. LNG implant users (Jadelle/Sino-plant) were 0.51 times as likely to become pregnant as ETG implant users (95% CI: 0.33–0.79, p<0.01). The likelihood of pregnancy decreased with increasing maternal age; the pregnancy IRRs were 0.61 (95% CI: 0.35–1.06) among 25–34 year-olds and 0.34 (95% CI: 0.18–0.62, p<0.01) among women >35 years of age, using 15–24 year-olds as the reference group.

Analysis of implant and ART combination showed that the pregnancy incidence rates among women using LNG implants with EFV and NVP or using a PI with either implant were significantly different from the reference population of ETG-EFV users.

Duration to failure curves (Figure 1) show that pregnancies began occurring within months of concurrent use, steadily accumulating thereafter. The shortest time to pregnancy was 94 days (16.5% and 48.7% within 6 and 12 months, respectively). ETG implant users had more early pregnancies than LNG implant users, but this is likely correlated with higher overall pregnancy incidence and shorter approved duration of use.

Figure 1. Contraceptive implant failure estimates.

ART, antiretroviral therapy; NVP, nevirapine; EFV, efavirenz; ETG, etonogestrel; LNG, levonorgestrel; PI, protease inhibitor.

As shown in Figure 2, the distribution does show skewing of our sample towards shorter periods of co-administration, given that the rise in implant use in Kenya is a recent phenomenon. The median duration of implant and ART co-administration in our dataset is 1.33 years (not shown).

Figure 2. Years of concurrent implant and ART use.

ART, antiretroviral therapy.

The sensitivity analysis among women aged 15–34 resulted in slightly higher pregnancy incidence (6.89 per 100 person-years [CI: 5.69–8.35]). Other results remained similar, except IRRs for LNG-NVP and LNG-EFV combinations compared to ETG-NVP were no longer statistically significant. This suggests a lack of robustness in differences across drug-drug combinations, a likely artifact of higher use of ETG implants by younger women.

Limitations

Retrospective studies can be limited due to issues of reliability and completeness of medical charts. Prospective studies with more frequent and standardized timing of follow-up could address some of these limitations. Prospectively capturing data could also allow for further analysis of drug-drug interactions with either ART or implants, such as rifampicin for TB or artemether-lumefantrine for malaria. However, the necessary financial investment and length of time would be substantial.

Our retrospective chart review had intended to measure multiple factors, including stage of HIV disease and other drug interactions; however, incompleteness of medical records did not allow for adequate analysis to answer these questions. We had also hoped to draw conclusions about timing of failure over time. However, because of recent expansion in use of implants in Western Kenya, most of the implant users in our data set had relatively a short duration of concurrent use with ART.

Biases may have also been introduced to the results because of variations in how RAs assessed abstracted records, due to the differing record management systems in the study facilities. Given the limitations in completeness of charts in the CCCs, the RAs diligently sought evidence of pregnancies in other units of the facilities, but it is difficult to do this systematically across diverse facilities.

Implications for practice

Women should be afforded choices when selecting FP and ART. However, women are generally unable to choose their ART. EFV is a safe, effective drug and will not be phased out soon as a first-line HIV treatment. Additionally, many countries still have a number of WLHIV using NVP, despite its continued phase out. In 2016, WHO included dolutegravir (DTG) as an alternative drug for first-line regimens, which became available in Kenya in 2017³³. Co-administration with implants has not been studied, although an interaction is unlikely, as DTG is not expected to significantly inhibit or induce CYP450 enzymes. Though DTG shows promise for women who wish to use contraceptive implants, concerns about potential birth defects has led to recommending that women of reproductive age be offered EFV instead. Results from a study in Botswana by Westhoff to assess change in ETG plasma levels among ETG implant users taking DTG are expected in late 2019^34,35.

It remains challenging to incorporate the results of this study into service delivery for WLHIV. It is premature to discourage women from adopting implants. However, women on NNRTIs need information, in simple, yet accurate language, about the drug interaction and possibility of method failure. Experiences in South Africa have demonstrated the difficulties in ensuring providers understand these drug interactions and are comfortable sharing information with clients²⁴. One option is to refer to the tier of effectiveness³⁶, but explain that for women on certain ART regimens, the implant falls somewhere in the middle tier of effectiveness: slightly better than pills or injectables, but less effective than IUDs or sterilization. Women should retain the right to make fully informed decisions about which contraceptive option works best for them and what level of method failure risk is acceptable, given that they cannot switch ART regimen based on their fertility preferences. Ideally, building a client-centered culture would allow WLHIV desiring control over their fertility to be offered DTG concurrently with an implant or other LARC.

At minimum, programs should encourage better documentation of all medications in medical charts. Health systems should establish mechanisms to track adverse events (pregnancies) in WLHIV using ART. Study facilities had ongoing efforts to integrate FP within HIV care and treatments services. Fully integrating FP services by including LARCs within services for WLHIV may improve care. Health systems should also ensure that IUDs are as accessible as implants and remove barriers to sterilization services. Research into the benefits and costs of alternative service delivery models could inform national policies.

In conclusion, implants are highly effective; however, clients using a NNRTI-containing ART regimen need additional information about higher incidence of pregnancies when used in combination with ARVs to allow them to make informed decisions about contraceptive options.

Underlying data

The dataset analyzed for this study was generated from client medical records under ownership of the Kenyan Ministry of Health. The authors’ permission to study this data does not extend to publically sharing the full dataset without prior permissions from the Kenyan Ministry of Health. Access to the de-identified dataset may be obtained by submitting a request to the Kenyan Medical Research Institute (KEMRI) (seru@kemri.org) and the Jhpiego Open Data Help team (OpenDataHelp@jhpiego.org), copied to anne.pfitzer@jhpiego.org, with a detailed description of the intended use and an IRB-approved protocol for secondary data analysis. Data will be provided under the condition that researchers have provided the required permissions from the Kenyan National AIDS Control Program and KEMRI.