Immune checkpoint inhibitors (ICI) revolutionized cancer therapy by augmenting anti-tumor immunity via cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed death-1/programmed death-ligand 1 (PD-1/PD-L1). However, this breakthrough is accompanied by immune-related adverse effects (irAEs), including renal complications. ICI-related nephritis involves complex mechanisms like auto-reactive T cells, auto-antibodies, reactivation of drug-specific T cells, and cytokine-driven inflammation culminating in AKI. ICI-AKI typically manifests weeks to months into treatment, often with other irAEs. Timely detection relies on monitoring creatinine levels and urine characteristics. Biomarkers, like soluble interleukin-2 receptor (sIL-2R) and urine cytokine levels, provide non-invasive insights, while renal biopsy remains the gold standard for confirmation. Management of ICI-AKI requires a balance between discontinuing ICI therapy and prompt immunosuppressive intervention, typically with corticosteroids. Some cases permit ICI therapy resumption, but varying renal recovery rates highlight the importance of vigilant monitoring and effective therapy. Beyond its clinical implications, the potential of irAEs to predict positive treatment responses in certain cancers raises intriguing questions. Data on nephritis–treatment response links are limited, and ongoing research explores this complex interaction. In summary, ICI therapy’s transformative impact on cancer treatment is counterbalanced by irAEs, including nephritis. Early recognition and management are vital, with ongoing research refining diagnostic and treatment strategies.

PURPOSE: Many factors contribute to long wait times for patients on the day of their chemotherapy infusion appointments. Longer wait time leads to nonoptimal care, increased costs, and decreased patient satisfaction. We conducted a quality improvement project to reduce the infusion wait times at a Comprehensive Cancer Center. METHODS: A multidisciplinary working group of physicians, infusion center nurses, pharmacists, information technology analysts, the Chief Medical Officer, and patient advocates formed a working group. Wait times were analyzed, and the contributing factors to long wait time were identified. Plan-Do-Study-Act cycles were implemented and included labeling patients ready to treat earlier, loading premedications into the medication dispensing system, increasing the number of pharmacy staff, and improving communication using a secure messaging system. The outcome measure was time from patient appointment to initiation of first drug at the infusion center. The secondary outcome measure was patient wait time satisfaction on the basis of Press Ganey score. RESULTS: Postintervention, the mean time from appointment to initiation of first drug decreased 17.6 minutes ( P < .001; 95% CI, 16.3 to 18.9), from 58.1 minutes to 40.5 minutes (43.5% decrease). Patient wait time satisfaction score increased 8.9 points ( P < .001; 95% CI, 6.0 to 11.82), from 76.2 to 85.1 (11.7% increase). CONCLUSION: Exploring real-time data and using a classic quality improvement methodology allowed a Comprehensive Cancer Center to identify deficiencies and prevent delays in chemotherapy initiation. This significantly improved patient wait time and patient satisfaction.