Case reports suggest that lopinavir/ritonavir, atazanavir, and ritonavir may be associated with tenofovir-associated kidney abnormalities [3,8,9,11,12,18,29,30]. It has been suggested that concurrent atazanavir or lopinavir/ritonavir may increase serum concentrations of tenofovir [35–37], and ritonavir may increase proximal tubule tenofovir concentrations . Others have suggested that patients treated with lopinavir/ritonavir often have more advanced HIV disease and thus a higher risk of adverse events . Our results agree with two prior studies that found no increase in tenofovir-associated kidney dysfunction among patients receiving lopinavir/ritonavir, atazanavir, or ritonavir [13,20]. However, we found a significant association between the coadministration of amprenavir and tenofovir and a decline in GFR, which has not been previously reported. We suspect that prior cohort studies have not detected this association because of the more limited use of amprenavir compared with, for example, lopinavir/ritonavir in many clinical settings. The basis for this association is unclear and additional studies are needed to confirm our findings as well as to examine possible mechanisms. Further characterization of interactions between amprenavir and drug efflux transporters may provide insight into mechanisms for this finding.
Reference methods for measuring GFR such as inulin are not suitable for routine clinical care . Therefore, clinicians rely on GFR estimates from equations incorporating clinical and demographic characteristics and serum creatinine. The validity of these equations has not been well established among HIV-infected patients . Single-sample serum creatinine level is the most widely used indirect estimate of GFR . However, creatinine levels are insensitive to even substantial declines in GFR , especially among individuals with HIV . The K/DOQI guidelines state that creatinine levels alone should not be used to assess kidney function . Despite their limitations, estimates of GFR using the CG and MDRD equations provide substantial improvement over just using serum creatinine .
We chose change in K/DOQI category as our primary measure of decline in GFR because both CG and MDRD equations have decreased accuracy at higher levels of GFR . A limitation of this approach is that small decreases in GFR in patients whose baseline value is close to a category cut-off will result in a category drop. We therefore conducted additional analyses requiring a change in category plus a decline in GFR of ≥ 20 ml/min per 1.73 m2. We also examined percentage change in GFR to decrease the impact of increased measurement variability of the CG and MDRD equations at higher levels of GFR . We used estimated GFR based on last creatinine value rather than an average value to maximize sensitivity of detecting decreasing levels over time. Another limitation of the CG equation is decreased accuracy among people with unusual body morphologies, such as those with obesity  or substantial muscle wasting . To explore this, we performed sensitivity analyses using the CG equation adjusted for body surface area and found no differences. Nevertheless, the impact of lipodystrophy (lipoatrophy and/or lipohypertrophy) on estimates of GFR will require additional studies.
The primary distinction between the CG and MDRD estimates of GFR is the inclusion of weight in the CG equation. The MDRD has been shown to overestimate GFR in underweight individuals , underestimate GFR at high GFR levels, and overestimate GFR at low levels . The CG equation may overestimate GFR at low GFR levels  and among patients with higher BMI . Therefore, using either equation for HIV-infected patients, who may have wide fluctuations in weight during the course of their disease, is problematic. Guidelines for HIV-infected individuals do not recommend the use of one method over the other .
Notably, the CG and MDRD equations identified groups of patients with kidney dysfunction that only partly overlapped (Fig. 1). Only four of the seven patients with severe kidney dysfunction identified by the CG equation were detected using the MDRD equation. Studies comparing the accuracy of the MDRD and CG formulae have been conducted in other patient populations, with mixed results that tended to favor MDRD [34,50,53–55]. The CG equation may provide a better estimate of GFR in HIV-infected patients, however, since it incorporates changes in weight commonly seen in this patient population. It is possible that the CG equation is imperfectly impacted by weight and that a decline in kidney function estimated by this method might represent changes in weight during follow-up. The findings were generally unchanged, however, when we accounted for change in weight in the multivariate model.
Strengths of our study included the ability to examine the comprehensive clinical data and the accurate antiretroviral treatment data captured in the UWHIS. Patients seen in routine care are more heterogeneous than those who enroll in clinical trials and have a broader range of characteristics and comorbid conditions. It is important to examine the effects of these characteristics on the outcome of tenofovir-associated kidney dysfunction and to determine the impact of these factors in real-world settings. As the cohort continues to be followed, additional information will become available with which to examine the effects of newer antiretroviral agents.
This study had a number of limitations. As with any observational study, unknown or unmeasured confounding is a concern. This was minimized by evaluating changes over time within individuals rather than comparing tenofovir-exposed patients with controls. Bias may be introduced by differences in the frequency of laboratory measurements in the clinical setting, but in our study, creatinine levels were routinely collected at 3–6 month intervals in the outpatient setting. Urine protein and phosphate levels were not routinely collected in the clinic and so were not available for analysis. The weights used in the CG equation were collected in a clinical setting by nursing staff prior to appointments, which may have resulted in less precision than weights collected using a research-based protocol. While the presence of HCV was noted, defined by the presence of HCV antibody or HCV RNA, we were unable to categorize HCV disease severity. Estimates of GFR relied on the use of the CG and MDRD equations but neither has been well validated among HIV-infected patients. Finally, we lacked any information regarding other potential risk factors that might impact tenofovir-related kidney dysfunction, such as genetic factors.
The authors thank Dr Ashley Jefferson for his suggestions and the staff and patients of the University of Washington Harborview HIV clinic.
Sponsorship: This work was supported by grants from the Mentored Patient-Oriented Research Career Development Award NIAID Grant (AI-060464) and the University of Washington Center for AIDS Research NIAID Grant (AI-27757).
No authors have any affiliation with or financial involvement in any organization, matter, or materials discussed in this manuscript.
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