Citations

Abstract BACKGROUND Preclinical studies have demonstrated that IDH1-mutant (IDHmt) gliomas harbor a BRCAness phenotype with a defect in homologous recombination that confers PARP inhibitor sensitivity. METHODS The phase II component of ABTC 1801 examined the efficacy of the combination of pamiparib (BeiGene BGB-290) with low dose metronomic temozolomide in recurrent IDHmt grade 2 and 3 gliomas. In this two-stage design, Arm A enrolled patients who had failed two lines and Arm B a single line of alkylator therapy. Pamiparib and temozolomide doses based on phase I results was 60 mg BID and 20 mg daily. Primary endpoint was objective response rate (ORR). RESULTS 39 patients (Arm A 15, Arm B 24) enrolled in the phase II. Median age was 45 (range: 25-69), 56% male, and median KPS 90. 72% of tumors were MGMT methylated. There were no confirmed responses in Arm A and one in Arm B; neither arm met the threshold for additional accrual. One-third of subjects discontinued treatment for reasons other than progressive disease. Estimated median PFS was 5.8 months in Arm A and 11.3 months in Arm B. Seven subjects (Arm A 3, Arm B 4) developed DLT during treatment. Grade 3+ toxicity was principally hematologic; 9 patients had grade 3 anemia, 7 grade 3 and 3 grade 4 neutropenia, and 3 grade 3 thrombocytopenia. In enhancing and non-enhancing tumors from 8 surgical arm patients, median unbound drug tumor/plasma ratios were 0.98 and 0.92, respectively; and median unbound pamiparib tumor concentrations were 209 and 188 nmol/L (or nmol/kg), respectively, which were >20-fold the in vitro IC50 for PARP inhibition. CONCLUSIONS While pamiparib appeared to achieve sufficient pharmacologically active concentrations in both enhancing and non-enhancing tumors, combination with temozolomide did not produce a meaningful ORR in IDHmt recurrent gliomas. Cumulative hematologic toxicity was substantial.

Abstract PURPOSE Hippocampal volume (HV) is a predictor of neurocognitive function (NCF) in neurodegenerative disease. The role of patient-specific anatomic variables has not been well investigated in patients with brain metastases. This work aimed to evaluate HV at baseline and 6 months as a predictor of NCF and differential benefit from HA-WBRT for patients enrolled on CC001. MATERIALS HV was calculated at baseline and 6 months. HV at baseline and 6 months were correlated with baseline and 2, 4, and 6-month NCF scores (HVLT-R Total and Delayed Recall, Delayed Recognition, TMT Parts A and B, and COWA) using Pearson correlation. Correlation was defined as weak if ρ ≤0.35. A cox proportional hazards model was used to determine the impact of baseline HV on time to NCF failure. RESULTS Of 518 patients randomized on CC001, 277 had baseline imaging, and 135 had 6-month imaging. However, only 87 patients were analyzable at both baseline and 6-month periods. At baseline, HV was not significantly associated with NCF score for any measure (p-value range: 0.06-0.72). Additionally, there was no association between baseline HV and time to NCF failure (p = 0.16). Additionally, the impact of treatment arm allocation on HV was examined but found to be non-significant (p = 0.06). Lastly, baseline HV and NCF scores were noted to have weak correlation at 2, 4, 6, and 12 month timepoints (ρ: range, -0.17-0.15; P-value range, 0.04-0.98). At 6 months, the correlation between HV, baseline NCF change, and 6 month standardized NCF change were also noted to be weak (ρ: range, 0.05-0.16; P-value range, 0.06-0.76). CONCLUSIONS Radiotherapy is known to have deleterious effects on neurocognition. In neurodegenerative disease, HV and rate of HV change are known predictors for NCF. However, baseline HV is not an independent predictor of neurocognitive changes after WBRT or HA-WBRT for patients with brain metastases.

Abstract Stereotactic radiation therapy yields high rates of local control for brain metastases, but patients in rural or suburban areas face geographic and socioeconomic barriers to its access. We conducted a phase II clinical trial of frameless, fractionated stereotactic radiation therapy for brain metastases in an integrated academic satellite network for patients 18 years of age or older with 4 or fewer brain metastases. Dose was based on gross tumor volume: less than 3.0 cm, 27 Gy in 3 fractions and 3.0 to 3.9 cm, 30 Gy in 5 fractions. Median follow-up was 10 months for 73 evaluable patients, with a median age of 68 years. Median intracranial progression-free survival was 7.1 months (95% confidence interval = 5.3 to not reached), and median survival was 7.2 months (95% confidence interval = 5.4 to not reached); there were no serious adverse events. Outcomes of this trial compare favorably with contemporary trials, and this treatment strategy provides opportunities to expand stereotactic radiation therapy access to underserved populations.

Background: Immune checkpoint inhibitors (ICIs) are a first-line and perioperative treatment for lung cancer. Pneumonitis is a potentially life-threatening complication of ICI treatment in 2% to 5% of patients; however, risk factors for developing ICI pneumonitis (ICI-p) remain undefined. Methods: We conducted a retrospective cohort study of consecutive patients with lung cancer who received at least one dose of ICI from 2015 through 2020 at The Ohio State University. Pneumonitis cases were documented by the treating oncologist and retrospectively evaluated for agreement between an oncologist and a pulmonologist. Patient demographic and clinical characteristics were recorded and summarized between those with and without pneumonitis for the overall cohort. Univariate and multivariable survival analyses using the Fine-Gray competing risk model were used to examine the associations. Results: A total of 471 patients with lung cancer were included, of which 402 had non–small cell lung cancer and 69 had small cell lung cancer; 39 (8%) patients in the overall cohort developed ICI-p. Preexisting interstitial abnormalities and prior chest radiation were both significantly associated with ICI-p on univariate analysis (hazard ratio [HR], 8.91; 95% CI, 4.69–16.92; P<.001; and HR, 2.81; 95% CI, 1.50–5.28; P=.001). On multivariable analyses, interstitial abnormalities remained a strong independent risk factor for ICI-p when controlling for chest radiation and type of immunotherapy (HR, 9.77; 95% CI, 5.17–18.46; P<.001). Among patients with ICI-p (n=39), those with severe (grade 3–5) pneumonitis had worse overall survival compared with those with mild (grade 1 or 2) pneumonitis (P=.001). Abnormal pulmonary function test results at both 12 and 18 months prior to ICI initiation were not significantly associated with ICI-p. Conclusions: Preexisting interstitial abnormalities on chest CT and prior chest radiation are independent risk factors that are strongly associated with ICI-p in patients with lung cancer. These findings highlight a potential need for closer observation for ICI-p among patients with these risk factors.

ABSTRACT How cell metabolism regulates DNA repair is incompletely understood. Here, we define a GTP-mediated signaling cascade that links metabolism to DNA repair and has significant therapeutic implications. GTP, but not other nucleotides, regulates the activity of Rac1, a guanine nucleotide-binding protein, which promotes the dephosphorylation of serine 323 on Abl-interactor 1 (Abi-1) by protein phosphatase 5 (PP5). Dephosphorylated Abi-1, a protein previously not known to activate DNA repair, promotes nonhomologous end joining. In patients and mouse models of glioblastoma, Rac1 and dephosphorylated Abi-1 mediate DNA repair and resistance to standard-of-care genotoxic treatments. The GTP–Rac1–PP5–Abi-1 signaling axis is not limited to brain cancer, as GTP supplementation promotes DNA repair and Abi-1-S323 dephosphorylation in nonmalignant cells and protects mouse tissues from genotoxic insult. This unexpected ability of GTP to regulate DNA repair independently of deoxynucleotide pools has important implications for normal physiology and cancer treatment. SIGNIFICANCE: A newly described GTP-dependent signaling axis is an unexpected link between nucleotide metabolism and DNA repair. Disrupting this pathway can overcome cancer resistance to genotoxic therapy while augmenting it can mitigate genotoxic injury of normal tissues. This article is featured in Selected Articles from This Issue, p. 5

The exponential growth of artificial intelligence (AI) has allowed for its integration into multiple sectors, including, notably, healthcare. Chatbots have emerged as a pivotal resource for improving patient outcomes and assisting healthcare practitioners through various AI-based technologies. In critical care, kidney-related conditions play a significant role in determining patient outcomes. This article examines the potential for integrating chatbots into the workflows of critical care nephrology to optimize patient care. We detail their specific applications in critical care nephrology, such as managing acute kidney injury, alert systems, and continuous renal replacement therapy (CRRT); facilitating discussions around palliative care; and bolstering collaboration within a multidisciplinary team. Chatbots have the potential to augment real-time data availability, evaluate renal health, identify potential risk factors, build predictive models, and monitor patient progress. Moreover, they provide a platform for enhancing communication and education for both patients and healthcare providers, paving the way for enriched knowledge and honed professional skills. However, it is vital to recognize the inherent challenges and limitations when using chatbots in this domain. Here, we provide an in-depth exploration of the concerns tied to chatbots’ accuracy, dependability, data protection and security, transparency, potential algorithmic biases, and ethical implications in critical care nephrology. While human discernment and intervention are indispensable, especially in complex medical scenarios or intricate situations, the sustained advancements in AI signal that the integration of precision-engineered chatbot algorithms within critical care nephrology has considerable potential to elevate patient care and pivotal outcome metrics in the future.

Background and Objectives: Literature reviews are foundational to understanding medical evidence. With AI tools like ChatGPT, Bing Chat and Bard AI emerging as potential aids in this domain, this study aimed to individually assess their citation accuracy within Nephrology, comparing their performance in providing precise. Materials and Methods: We generated the prompt to solicit 20 references in Vancouver style in each 12 Nephrology topics, using ChatGPT, Bing Chat and Bard. We verified the existence and accuracy of the provided references using PubMed, Google Scholar, and Web of Science. We categorized the validity of the references from the AI chatbot into (1) incomplete, (2) fabricated, (3) inaccurate, and (4) accurate. Results: A total of 199 (83%), 158 (66%) and 112 (47%) unique references were provided from ChatGPT, Bing Chat and Bard, respectively. ChatGPT provided 76 (38%) accurate, 82 (41%) inaccurate, 32 (16%) fabricated and 9 (5%) incomplete references. Bing Chat provided 47 (30%) accurate, 77 (49%) inaccurate, 21 (13%) fabricated and 13 (8%) incomplete references. In contrast, Bard provided 3 (3%) accurate, 26 (23%) inaccurate, 71 (63%) fabricated and 12 (11%) incomplete references. The most common error type across platforms was incorrect DOIs. Conclusions: In the field of medicine, the necessity for faultless adherence to research integrity is highlighted, asserting that even small errors cannot be tolerated. The outcomes of this investigation draw attention to inconsistent citation accuracy across the different AI tools evaluated. Despite some promising results, the discrepancies identified call for a cautious and rigorous vetting of AI-sourced references in medicine. Such chatbots, before becoming standard tools, need substantial refinements to assure unwavering precision in their outputs.