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HIV-ASSIST in India
Cases in Care: HIV-ASSIST in India

Released: June 19, 2025

Expiration: June 18, 2026

Manish Bamrotiya
Manish Bamrotiya, MBBS, FHM
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Key Takeaways
  • HIV-ASSIST is a guideline-based decision support tool designed to simplify decision-making in HIV care, providing dosing specifics, guideline evidence, and information on drug interactions in one centralized tool.
  • HIV-ASSIST is also a comprehensive tool for addressing complex cases: It considers infection characteristics, patient preferences, and even drug availability to recommend optimized ART regimens.   

India’s HIV landscape is undergoing a transformation, with broader access to testing and treatment revealing new complexities such as tuberculosis (TB)/HIV coinfections and virologic failures driven by adherence challenges. Primary care providers are increasingly involved in addressing these issues along with specialists, navigating the unique needs of people living with HIV. With my background as a primary care provider, I have observed how HIV-ASSIST, a decision support tool, proves to be invaluable across care settings by simplifying antiretroviral therapy (ART) decisions. 

Through 2 detailed examples from the field, I illustrate how it supports optimal treatment planning.

A Common Encounter: TB/HIV Coinfection
TB stands out as the most common opportunistic infection among people living with HIV in India, a scenario any healthcare professional might face.

One such case involved a 34-year-old man diagnosed with HIV and pulmonary TB, already receiving rifampicin-based anti-TB treatment that began 5 days prior. His CD4+ cell count was 156 cells/mm³, reflecting advanced disease, although HIV-1 RNA and genotyping data were unavailable. He experienced a persistent cough with sputum production for 2 months, night sweats, a low-grade fever of 38°C, weight loss of 8 kg over 4 months, fatigue, and generalized weakness, with no neurologic symptoms or signs of extrapulmonary TB.

He has a history of smoking (10 pack-years) and occasional alcohol use. Laboratory results showed mild anemia with a hemoglobin of 11.5 g/dL, mildly elevated liver function tests with an alanine aminotransferase of 55 U/L (normal range: 10-40 U/L) caused by the treatment, a serum creatinine of 1.0 mg/dL, and a fasting blood sugar of 95 mg/dL—all normal.

My task was to initiate ART while navigating rifampicin’s drug interactions.

Without HIV-ASSIST, this required extensive guideline reviews. But with HIV-ASSIST, inputting his details—CD4+ cell count <200 cells/mm³ and TB treatment with rifampicin, pyrazinamide, ethambutol and isoniazid—into the tool yielded dolutegravir (DTG) plus tenofovir (TDF)/lamivudine (3TC) with a score of 2.5, indicating strong to moderate evidence (the lower the score, the higher the recommendation ranking).

Aligned with the National AIDS Control Organisation (NACO) and WHO guidelines, it recommended DTG as a first-line option, with rifampicin’s interaction managed by a 50-mg twice-daily dose during TB treatment. TDF/3TC, widely accessible, posed minimal interaction risks.

The information sheet is a vital resource, providing dosing specifics, guideline evidence, and a rationale that explains why alternatives like efavirenz (EFV) (score 3.5) or protease inhibitors (score >5) were less ideal owing to hepatotoxicity and drug interactions. This enables primary care providers to select an optimal regimen efficiently, in all types of cases, and follow-up in similar cases showed significant HIV-1 RNA reductions, validating the tool’s impact.

Resistance and Adherence
A particularly notable case involved a 37-year-old woman receiving tenofovir/lamivudine (3TC)/EFV who had an HIV-1 RNA of 6000 copies/mL after prior suppression, with a CD4+ cell count of 370 cells/mm³. Genotyping revealed M184V and K103N mutations, indicating resistance to 3TC/emtricitabine (FTC) and EFV/nevirapine, respectively, reflecting nuances of her treatment history on a nonnucleoside reverse transcriptase inhibitor–based regimen before switching to T/3TC/EFV. She reported poor adherence (60%) because of nausea and fatigue from T/3TC/EFV, influenced by a busy lifestyle, with a BMI of 18 kg/m².

Her complete blood count was normal, serum creatinine was 0.7 mg/dL, and she tested negative for hepatitis B and C viruses, with an HLA-B*5701–negative status. The treatment history revealed a shift from an earlier regimen, adding complexity, but the need was to adjust therapy effectively.

Even for those frequently involved in HIV care, managing such resistance and adherence issues felt daunting. HIV-ASSIST simplified this. I could input her data: M184V and K103N mutations, low HIV-1 RNA, CD4+ cell count >200 cells/mm³, and T/3TC/EFV adverse events. Adherence details, such as her 60% adherence rate, were also entered into the tool, influencing the recommendation toward regimens with better tolerability, as noted in the information sheet’s rationale.

The top recommendations from the tool included TDF/3TC/DTG, TAF/FTC/DTG, or TAF/FTC/bictegravir (BIC), all with score 0.2 showing strong evidence and consistent with WHO and NACO’s second-line guidance. The rationale highlighted the high resistance barrier of DTG or BIC (no integrase strand transfer inhibitor mutations), renal safety of TAF, and continued use of FTC/3TC despite M184V for residual activity, while avoiding EFV to improve tolerability.

Of note, HIV-ASSIST’s strength shines even when genotyping data are unavailable. If for the same case the genotype were unavailable, the tool considers archived mutations—those accumulated from previous treatments like T/3TC/EFV—and still recommends TDF/3TC/DTG or TAF/FTC/BIC or TAF/FTC/DTG as the optimal regimens.

This is extremely helpful in settings where genotyping is not routinely accessible, allowing healthcare professionals to rely on treatment history alone. It saves time and ensures consistent care, making it a lifeline for those with limited HIV expertise who can confidently adjust therapy based on this insight. The information sheet is key, offering detailed dosing, evidence, and a rationale that explains penalties for alternatives. This allows informed decisions, even with limited HIV expertise. 

My Experience
India’s changing HIV care demands tools that bridge primary and specialized settings. HIV-ASSIST delivers by integrating guidelines, drug interactions, and patient factors into practical insights. Its information sheets detailing dosing, evidence, and rationale empower primary care providers to handle common HIV cases and support specialists with nuanced treatment histories.

From my experience, it enhances decision-making efficiency and confidence, aligning with the 95-95-95 goals. I encourage healthcare professionals to explore HIV-ASSIST at www.hivassist.com. It is essential for optimizing HIV care across India.

Your Thoughts
How do you optimize HIV treatment in your practice? Leave a comment to join the discussion!