Renal cell carcinoma (RCC) is the most common kidney cancer in adults (approximately 90%), and clear cell RCC (ccRCC) is the most frequent histologic subtype (approximately 75%). We reviewed the safety and efficacy of checkpoint inhibitors (CPIs) in ccRCC, identifying 5927 articles in PubMed, Embase, Cochrane, and Web of Science. Ten randomized control (N = 7765) and 10 non-randomized (N = 572) studies were included. Overall, 4819 patients treated with CPI combinations were compared with everolimus, sunitinib, or placebo. Overall response rates (ORR) were 9–25% with nivolumab (niv), 42% with niv + ipilimumab (ipi), 55.7% with niv + cabozantinib, 56% with niv + tivozanib vs. 5% with everolimus. ORR was 51.5–58% with avelumab + axitinib vs. 25.5% with sunitinib. ORR was 59.3–73% with pembrolizumab + tyrosine kinase inhibitor vs. 25.7% with sunitinib. ORR was 32–36% with atezolizumab + bevacizumab vs. 29–33% with sunitinib. In patients with PD-L1+ve and -ve ccRCC, niv, atezolizumab, ipi, and pembrolizumab were safe and effective alone and when combined with cabozantinib, tivozanib, axitinib, levantinib, and pegilodecakin. Atezolizumab + bevacizumab was safe and effective in ccRCC with high PD-L1 expression. Pembrolizumab was safe and effective in preventing recurrence in ccRCC patients with nephrectomy. Additional randomized, double-blind, multicenter clinical trials are needed to confirm these results.

In December 2021, we searched for publicly available posts using the terms "hepatitis b" and "hep b". We removed duplicates from the top 55 posts for each term and coded N5103 posts using a validated misinformation codebook with 72 variables including: engagement (e.g., number of likes), user characteristics (e.g., # of followers, # following), profitability (e.g., for profit, selling product or service), and claims with misinformation (determined by medical experts). We applied two-tailed z-tests, chi-square tests, and linear regressions to examine associations between profitability and misinformation (outcome). Results: Nearly a quarter of posts (n524, 23%) contained misinformation about hepatitis B and/or hepatitis B treatment. Misinformation posts had more engagement on average (1,599 likes vs. 970 likes, p, 0.01), were following more accounts (1,127 vs. 889, p5, 0.01), but had fewer followers (mean: 22,920n vs. 70,442, p, 0.001) than accurate posts. Nearly one-third of posts about hepatitis B referenced a conspiracy theory (30%), were for-profit (29%), and were selling a product or service (34%) through Instagram. Significantly more misinformation posts were for profit (47% vs. 14%, p, 0.01) and were selling a product or service (43% vs. 13% p, 0.01) compared to accurate posts. For-profit accounts (b5713, 95% CI 25-1401, p50.04) and those selling a product or service (b5843, 95% CI 196-1490, p50.01) were following significantly more accounts than their counterparts. Conclusion: Online health misinformation poses direct threat to patients and has broader reach and engagement than accurate information. Hepatitis B misinformation may exacerbate health disparities, given that financial incentives are difficult to distinguish, however our findings suggest that a high number of "following" accounts may be a marker for accounts seeking profitability off of Hepatitis B misinformation on Instagram. More research is needed to understand how exposure to health information can influence patient/caregiver behavior and downstream clinical and financial outcomes.