JCO Precision Oncology

PurposeThe addition of PARP inhibitors to chemotherapy has been assessed in [~]80 clinical trials across multiple malignancies, on the premise that PARP inhibitors will increase chemotherapy effectiveness regardless of whether cancers have underlying disruption of DNA repair pathways. Consequently, the majority of combination therapy trials have been performed on patients without biomarker selection, despite the use of homologous recombination deficiency to dictate use of PARP inhibitors in the maintenance setting. An unresolved question is whether biomarkers are needed to identify patients who respond to combination PARP inhibitors and chemotherapy. MethodsA systematic literature review identified studies using PARP inhibitors in combination with chemotherapy versus chemotherapy alone, where the study included a biomarker of DNA repair function (BRCA1, BRCA2, BRCAPRO, ATM, ERCC1, SFLN11). Hazard ratios (HR) were pooled in a meta-analysis using generic inverse-variance and fixed or random effects modelling. Subgroup analyses were conducted on biomarker selection and type of malignancy. ResultsNine studies comprising 2,084 patients met the inclusion criteria. Progression-free survival (PFS) was significantly better in patients with a DNA repair biomarker (HR 0.52, 95% confidence interval (CI) 0.43-0.63; p < 0.00001), but there was no benefit in patients who lacked a biomarker (HR 0.94, 95% CI 0.82-1.08; p = 0.38). Subgroup analysis showed that BRCA mutation and SFLN11 biomarkers could predict benefit, and biomarker-driven benefit occurred in ovarian, breast and small cell lung cancers. The addition of PARP inhibitors was associated with increased grade 3/4 side effects, and particularly neutropenia. ConclusionsCombination therapy only increases PFS in patients with identifiable DNA repair biomarkers. This indicates that PARP inhibitors do not sensitise patients to chemotherapy treatment, except where their cancer has a homologous recombination defect, or an alternative biomarker of altered DNA repair. While effective in patients with DNA repair biomarkers, there is a risk of high-grade haematological side-effects with the use of combination therapy. Thus, the benefit in PFS from combination therapy must be weighed against potential adverse effects, as individual arms of treatment can also confer benefit. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/23290442v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1c2dddcorg.highwire.dtl.DTLVardef@73d1e3org.highwire.dtl.DTLVardef@1d8cef0org.highwire.dtl.DTLVardef@fa22cc_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundPreclinical studies support targeting PI3K/AKT/mTOR signalling in platinum-resistant ovarian cancer (PROC). A phase I study of the dual mTORC1/mTORC2 inhibitor vistusertib with weekly paclitaxel (wP) showed activity. We report the results of Arm 1 of OCTOPUS, the first randomised trial of weekly paclitaxel and dual mTORC1/2 inhibition in ovarian cancer. MethodsPatients with platinum-resistant or refractory high grade serous carcinoma were randomised (1:1) to wP (80mg/m2 D1,8,15 of 28 day cycle) plus oral vistusertib (50mg BD) or placebo (P). The primary endpoint was progression-free survival (PFS). Secondary endpoints included response rate (RR) and overall survival (OS). Results140 patients (median age 63, range: 36-86; 18% platinum-refractory; 54% [&ge;]3 prior therapies) were randomised. There was no difference in PFS (median 4.5 vs 4.1m (HR 0.84; 80% CI (0.67, 1.07); 1-sided p=0.18), OS (median 9.7 vs 11.1m (HR 1.21; 80% CI (0.91, 1.60); 1-sided p=0.80) or RR (odds ratio 0.86; 80% CI (0.55, 1.36); 1-sided p=0.66). Grade 3/4 adverse events were 41.2% (wP+V) vs 36.7% (wP+P). Low tumour PTEN expression was associated with longer PFS in the wP+V arm (9.4 vs 4.1m p=0.003) but not in the wP arm (4.8 vs 4.2m p=0.60). Tumour genome-wide copy number (CN) analysis suggested that high CN signature 4 was associated with worse outcome in the wP+P arm (2.3 vs 4.6m p=0.018) but not the wP+V arm (5.4 vs 3.3m). ConclusionsVistusertib did not improve clinical activity of wP in PROC. However, low tumour cell PTEN expression may be a predictive biomarker for vistusertib activity. Translational RelevancePreclinical studies suggest that activation of the PI3K/AKT/mTOR signalling pathway contributes to platinum-resistance in ovarian high grade serous carcinoma (HGSC). Based on activity in a phase I study, we evaluated the clinical efficacy of the dual mTORC1/mTORC2 inhibitor vistusertib in combination with weekly paclitaxel in the OCTOPUS study - a multi-centre, randomised, placebo-controlled, phase II trial in platinum-resistant ovarian (HGSC). In the first randomised trial of weekly paclitaxel and dual mTORC1/2 inhibition in ovarian cancer, vistusertib did not improve clinical activity of weekly paclitaxel. However, translational analyses indicated that low tumour cell PTEN expression may be a predictive biomarker for vistusertib activity. We also showed genome-wide copy number (CN) analysis, in particular high exposure to CN signature 4, may also allow identification of patients with greater chance of benefit from dual mTORC inhibition. Potential predictive biomarkers identified in our study should be evaluated in ongoing/future studies.

The overwhelming majority of dose-escalation clinical trials use methods that seek a maximum tolerable dose, including rule-based methods like the 3+3, and model-based methods like CRM and EWOC. These methods assume that the incidences of efficacy and toxicity always increase as dose is increased. This assumption is widely accepted with cytotoxic therapies. In recent decades, however, the search for novel cancer treatments has broadened, increasingly focusing on inhibitors and antibodies. The rationale that higher doses are always associated with superior efficacy is less clear for these types of therapies. We extracted dose-level efficacy and toxicity outcomes from 115 manuscripts reporting dose-finding clinical trials in cancer between 2008 and 2014. We analysed the outcomes from each manuscript using flexible non-linear regression models to investigate the evidence supporting the monotonic efficacy and toxicity assumptions. We found that the monotonic toxicity assumption was well-supported across most treatment classes and disease areas. In contrast, we found very little evidence supporting the monotonic efficacy assumption. Our conclusion is that dose-escalation trials routinely use methods whose assumptions are violated by the outcomes observed. As a consequence, dose-finding trials risk recommending unjustifiably high doses that are harmful to patients. We recommend that trialists consider experimental designs that allow toxicity and efficacy outcomes to jointly determine the doses given to patients and recommended for further study.

PURPOSEPediatric supportive care trials frequently rely on analyses of multiple clinically relevant outcomes, posing challenges for overall trial interpretation. Hierarchical composite endpoints (HCEs) rank relevant outcomes by prespecified clinical importance and offer potential advantages such as harmonizing trial conclusions. METHODSWe reanalyzed two randomized supportive care trials utilizing post-hoc HCE, each conducted through the Childrens Oncology Group. ACCL0934 evaluated levofloxacin for prevention of bloodstream infection (BSI) in patients with acute leukemia (AL) or undergoing hematopoietic cell transplant (HCT) and was chosen because of observed multidimensional benefits of levofloxacin. ACCL0431 evaluated sodium thiosulfate (STS) for prevention of cisplatin-induced hearing loss. ACCL0431 analyses were performed for overall and localized disease subgroups, chosen due to conflicting effect directionality on hearing vs survival by cohort. We estimated treatment effects on HCEs using win-odds ratios (WO). For ACCL0934, the primary HCE included death, severe infection, BSI, and neutropenic fever. For ACCL0431, the HCE included death, relapse/progression, and hearing loss. RESULTSIn ACCL0934, levofloxacin reduced BSI incidence, but only with corresponding p-value <0.05 in the AL cohort (22% vs 43% on control; P=0.003; HCT: 11% versus 17% on control; P=0.06). Using HCE reanalysis, the estimated win-odds achieved statistical significance in both cohorts (AL: WO=1.74, P=0.002; HCT: WO=1.28, P=0.031). In ACCL0431, HCE analyses resulted in an estimated null effect (WO=1) in the overall cohort but resulted in beneficial effects (WO>1) for analyses of the localized cohort. CONCLUSIONHCEs can provide a harmonized framework for interpreting complex supportive care trials by integrating outcomes of varying clinical importance. These post-hoc analyses should not be used to reinterpret either trial but motivate consideration of prospective use of HCE going forward.

Novel pivotal trial designs, that more clearly demonstrate increased benefit over Standard of Care (SOC), especially in oncology and immuno-oncology (IO), are presented. The benefit of therapy is maximized and sample size is dramatically reduced. The novel methodology includes the introduction of a biochemical "Optimizing Diagnostic", for example a cfDNA test that can detect poor response, when performed early after therapy is begun; this is used to change the therapy of the tested person early in the trial (typically to SOC), before clinical progression. Patients remain in "the new drug first" group, which is compared to SOC. An "Optimizing Diagnostic" is analogous to a "Companion Diagnostic"; both potentially allow approval of drugs that would otherwise fail. A companion diagnostic predicts benefit prior to therapy, the optimizing diagnostic (more accurately) predicts likelihood of benefit after initial therapy. Those patients deemed less likely to respond remain in the novel drug first arm, but are switched to SOC. A Sequential Multiple Assignment Randomized Trial" (SMART) design is proposed to evaluate if switching to SOC or SOC plus continuing the novel therapy is most beneficial. These designs will allow approval of therapy paths including novel agents when the novel agent could not be approved without this design. A good optimizing test may reduce the number of patients needed by 80%, dramatically reducing cost and time; more patients benefit and accrual is easier. Key PointsO_LIA new clinical trial design focused on testing a path that begins with a novel regimen (IO is featured) is presented. C_LIO_LIThe path includes an "optimizing diagnostic" that determines, early during treatment, if a patient should remain on the new regimen. C_LIO_LICompanion diagnostics define the path at a pre-treatment stage, optimizing diagnostics define the path early during treatment. Changes in therapy, typically to the SOC, is made based on the post-test probability of success. C_LIO_LIThe novel path is significantly more likely to lead to approval than the novel regimen alone. C_LIO_LIUse of the novel method can reduce the size of a trial by 80%, and allow approval of the path, when approval of the novel regimen, based on a head-to-head trial vs SOC, would not be possible. C_LI

Most oncology trials define superiority of an experimental therapy compared to a control therapy according to frequentist significance thresholds, which are widely misinterpreted. Posterior probability distributions computed by Bayesian inference may be more intuitive measures of uncertainty, particularly for measures of clinical benefit such as the minimum clinically important difference (MCID). Here, we manually reconstructed 194,129 individual patient-level outcomes across 230 phase III, superiority-design, oncology trials. Posteriors were calculated by Markov Chain Monte Carlo sampling using standard priors. All trials interpreted as positive had probabilities > 90% for marginal benefits (HR < 1). However, 38% of positive trials had [&le;] 90% probabilities of achieving the MCID (HR < 0.8), even under an enthusiastic prior. A subgroup analysis of 82 trials that led to regulatory approval showed 30% had [&le;] 90% probability for meeting the MCID under an enthusiastic prior. Conversely, 24% of negative trials had > 90% probability of achieving marginal benefits, even under a skeptical prior, including 12 trials with a primary endpoint of overall survival. Lastly, a phase III oncology-specific prior from a previous work, which uses published summary statistics rather than reconstructed data to compute posteriors, validated the individual patient-level data findings. Taken together, these results suggest that Bayesian models add considerable unique interpretative value to phase III oncology trials and provide a robust solution for overcoming the discrepancies between refuting the null hypothesis and obtaining a MCID. SIGNIFICANCE STATEMENTThe statistical analyses of oncology trials are usually performed by calculating P values, although these are poorly understood. Using P value cutoffs, such as P < 0.05, may lead to some treatments being accepted which have little benefit, and other therapies being rejected which have considerable benefit. A more intuitive and direct probability-- that an experimental treatment is better than a standard treatment--can be calculated by Bayesian statistics. Here we used software to obtain the outcomes of 194,129 patients enrolled across 230 trials and then calculated probabilities of benefit. Interpretations based on P values disagreed with the probabilities of benefit in one-third of trials. This study suggests that probabilities of benefit would considerably enhance the interpretation of oncology trials.

The presence of measurable residual disease (MRD) is strongly associated with treatment outcomes in acute myeloid leukemia (AML). Despite the correlation with clinical outcomes, MRD assessment has yet to be standardized or routinely incorporated into clinical trials. Discrepancies have been observed between different techniques for MRD assessment and there remains a need to compare centralized, high-quality multiparametric flow cytometry (MFC) and ultrasensitive next-generation sequencing (NGS) in AML patients with diverse mutational profiles. In 62 patients with AML, aged 18-60, in first complete remission after intensive induction therapy on the randomized phase 3 SWOG-S0106 clinical trial, MRD detection by MFC was compared with a 29 gene panel utilizing duplex sequencing (DS), an NGS method that generates double-stranded consensus sequences to reduce false positive errors. Using DS, detection of a persistent mutation utilizing defined criteria was seen in 22 (35%) patients and was strongly associated with higher rates of relapse (68% vs 13% at year 5; HR, 8.8; 95% CI, 3.2-24.5; P<0.001) and decreased survival (32% vs 82% at year 5; HR, 5.6; 95% CI, 2.3-13.8; P<0.001). MRD as defined by DS strongly outperformed MFC, which was observed in 10 (16%) patients and marginally associated with higher rates of relapse (50% vs 30% at year 5; HR, 2.4; 95% CI, 0.9-6.7; P=0.087) and decreased survival (40% vs 68% at year 5; HR, 2.5; 95% CI, 1.0-6.3; P=0.059). Furthermore, the prognostic significance of DS MRD status at the time of remission was similar on both randomized arms of the trial, predicting S0106 clinical trial outcomes. These findings suggest that DS is a powerful tool that could be used in patient management and for early treatment assessment in clinical trials.

BackgroundPoly (ADP-ribose) polymerase inhibitors (PARPi) are effective in patients with germline BRCA 1/2 and PALB2 mutations but have been largely ineffective as monotherapy in others. PARP interacts with, and is recruited to, DNA damage sites along with epigenetic factors, such as DNA methyltransferase 1 (DNMT1). In addition to increasing PARP-trapping, inhibitors of DNMT modulate ROS-cAMP/PKA signaling and induce a pathogen mimicry, inflammasome signaling response and a BRCAness phenotype that further sensitizes cells to PARPi. In preclinical in vitro and in vivo studies, combined DNMTi + PARPi therapy was effective in both triple negative (TNBC) and hormone resistant (HRBC) models with intact BRCA. MethodsWe conducted a phase I study combining the oral DNMTi ASTX727 with the PARPi talazoparib in patients (pts) with previously treated TNBC or HRBC; pts with deleterious mutations of BRCA were excluded. Pts with TNBC had received at least one prior chemotherapy and pts with HRBC had received prior endocrine therapy with a cyclin-dependent kinase inhibitor for metastatic disease. An ECOG PS 0-1 and adequate organ function was required. A classical 3+3 design guided dose escalation/de-escalation with dose-limiting toxicity (DLT) defined as Grade 4 neutropenia or thrombocytopenia lasting [&ge;]7 days, or clinically significant grade [&ge;]3 non-hematologic toxicity in cycle 1; 28 days constituted each cycle. Serial peripheral blood mononuclear cells (PBMCs) were analyzed for changes in methylation using the Infinium Methylation EPIC BeadChip and LINE1 sequencing. Results34 evaluable pts were enrolled and treated in 8 dose cohorts. Median age was 59 years, 12% identified as Black. Myelosuppression was common with grade [&ge;]3 neutropenia in 42% and grade 3 anemia and thrombocytopenia in 13%. DLT was limited to neutropenia. Efficacy was assessed in 29 pts. There were no objective responses, 6 pts had stable disease persisting for > 4 months in 3 pts. LINE1 demethylation ranged from [~]2-10% and immune-specific CpGs (methylation in immune cells) changed 1-5% by differential methylation locus analysis at Day 15. Methylation changes were not dose dependent. ConclusionsASTX727 plus talazoparib produces significant myelosuppression but is otherwise well tolerated. Low dose ASTX727 (10 mg decitabine: 100 mg cedazuridine) on Days 1,3,5 with talazoparib 0.5 mg daily on Days 1-21 of each 28-day cycle is recommended for phase II trials. Methylation changes in PBMCs were detected and some heavily pre-treated pts had prolonged stable disease despite the attenuated doses. Statement of Translational RelevanceInhibitors of poly (ADP-ribose) polymerase (PARPi) have significant clinical benefit in patients with advanced breast cancer who harbor deleterious mutations of BRCA1, BRCA2, or PALB2 but have had limited benefit in those without mutations. Similarly, epigenetic therapies such as the DNA methyltransferase inhibitors (DNMTi) slow disease progression in some hematologic malignancies and myelodysplastic syndromes but have not found a role in solid tumors. Despite limited clinical activity as monotherapy, the combination of PARP and DNMTi significantly inhibited tumor growth in several preclinical models with intact BRCA. In the first clinical trial combining talazoparib and ASTX727, myelosuppression limited drug exposure but the combination was otherwise well tolerated. Strategies to reduce myelosuppression with this combination should be explored. Despite the attenuated doses, methylation changes in peripheral blood mononuclear cells (PMBCs) and clinical benefit were observed; neither were clearly dose dependent.

BackgroundCDK4/6 inhibitors is highly valued, but the incidence of cardiovascular events (CVAEs) associated with CDK4/6 inhibitors is not clear. MethodsEligible CVAEs were extracted from the ClinicalTrials.gov registry. A systematic search of electronic databases (PubMed, Embase, Cochrane Library, and important meetings) until 3 September 2023 was conducted. A disproportionality analysis was performed from the first quarter (Q1) of 2013 to Q1 of 2023 using data from the FDA Adverse Event Reporting System database. Study heterogeneitywas assessed using the I2 statistic. Using Peto OR and inverse variance methods to calculate the risk and incidence of CVAEs associated with CDK4/6 inhibitors. Findings21 RCTs and cohort trials (n=24,331) were included. During the follow-up period of 8.4 to 34.0 months, CDK4/6 inhibitors significantly increased the risk of CVAEs (Peto OR, 1.64, 95% confidence interval, 1.23 - 2.21, P < 0.01). The rates of QT prolongation and deep vein thrombosis were 98.83 (89.6-100.1) and 6.41 (5.23-7.18) per 1000 patients, respectively. Moreover, we identified 11 CVAEs that were not reported in RCTs or cohort studies, acute coronary syndrome, atrial fibrillation, and mobile thrombophlebitis etc. were strongly correlated with CDK4/6 inhibitors. Furthermore, the risk of CVAEs varied depending on the specific CDK4/6 inhibitors used, its combination with different endocrine therapies, and the patients treatment stage. InterpretationCDK4/6 inhibitors increase the risk of CVAEs, some of which may lead to serious consequences, early recognition and management of CVAEs is of great importance in clinical practice.

Myelodysplastic Syndrome (MDS) patients are at risk of relapse after allogeneic hematopoietic cell transplantation (alloHCT). The utility of ultra-deep genomic testing to predict, and the impact of conditioning intensity to prevent, MDS relapse are unknown. Targeted error-corrected DNA sequencing was performed on pre-conditioning blood samples from the Blood and Marrow Transplant Clinical Trials Network (BMT CTN) 0901 phase III randomized clinical trial which compared outcomes by alloHCT conditioning intensity in adult patients with less than 5% marrow myeloblasts and no leukemic myeloblasts in blood on morphological analysis at the time of pre-transplant assessment. Using a previously described set of 10 gene regions, 42% of patients had mutations detectable prior to randomization to reduced intensity or myeloablative conditioning. Testing positive was associated with increased rates of relapse and decreased overall survival. In those testing positive, relapse rates were higher and relapse-free survival was lower in reduced intensity versus myeloablative conditioning arms. Testing additional genes, including those associated with MDS, did not improve prognostication. This study provides evidence that post-transplant relapse rates in MDS patients are highest in those with pre-transplant genomic evidence of high-risk disease. In those testing positive, randomization to myeloablative conditioning lowered but did not eliminate relapse risk.

The prognostic value of nucleophosmin-1 (NPM1) and fms-like tyrosine kinase 3 (FLT3) mutations has been well-established in adult patients but is less clear in geriatric patients. This retrospective cohort study assessed adult patients with acute myeloid leukemia (AML) who received FLT3 and/or NPM1 testing treated at any Veterans Health Administration (VHA) facility or at Vanderbilt University Medical Center (VUMC) between January 2006 and December 2016. The primary analysis compared time to all-cause death among patients with AML based on FLT3 and NPM1 mutation status, age (<65 years, [&ge;]65 years), and cytogenetic risk group (unfavorable, intermediate/normal, favorable). The study population (n=766) (mean age 59.71 {+/-} 16.6 years, 45.96% [&ge;]65 years) had a mutation rate of 19.8% for FLT3 and 22.1% for NPM1. Age was a significant factor in overall survival (median OS: 24.28 vs. 8.18 months, p<0.001), as was cytogenetic risk status (median OS: favorable group not reached, intermediate/normal 17.61m vs. unfavorable 6.77m, p<0.001). The most favorable prognostic group (FLT3-/NPM1+) among older patients showed worse OS (15.21 months) than did the poor prognostic group (NPM1-/FLT3-) among younger patients (18.43 months). Among the older cohort, FLT3 and NPM1 mutation status, favorable karyotype, and CCI were not identified as prognostic factors. In the full cohort, using Cox proportional hazard regression and LASSO analyses for age, FLT3 and NPM1 mutation status, cytogenetic risk group, treatment site, race, primary payor, and Charleston Comorbidity Index (CCI), age (HR 65y vs 35y/=2.44, 95% CI 1.61-3.68, p<0.001) was the strongest risk factor in AML.

PURPOSEWe propose and demonstrate the feasibility and desirability of a novel model-free dose-finding design for phase I clinical trials. METHODSThe Generalized 3+3 (G3+3) design uses a set of simple rules summarized as follows: For 3 or 6 patients at a dose, apply the 3+3 design for making dosing decisions. For other numbers, if the observed toxicity rate (OTR) is less than 0.2, escalate to the next higher dose; if the OTR is greater than 0.29, de-escalate to the next lower dose; otherwise, stay at the current dose. RESULTSThe G3+3 design is the only design that can replicate the decisions of the 3+3 design for 3 or 6 patients among the popular designs compared like BOIN and i3+3. G3+3 generates desirable decisions when the number of patients treated is not 3 or 6, like the popular designs. Computer simulation verifies the superior operating characteristics of the G3+3 design. CONCLUSIONThe G3+3 design generalizes the popular 3+3 design so that desirable decisions can be made for any number of patients at a dose. G3+3 does not rely on statistical models, is simple and transparent, and can be implemented without a software tool. Therefore, it is expected to facilitate and enhance modern phase I dose-finding trials and early-phase drug development.

Backgroundrecurrent ovarian cancer (OC) patients with platinum-free interval (PFI) <6 mo. are usually considered platinum-resistant and treated with non-platinum based chemotherapy. However, this was never confirmed in proper-conducted randomized trials. Methodswe queried the PubMed database for all full-text articles and abstracts on the treatment of patients with platinum-resistant ovarian cancer (PROC) in 01/01/2000-01/06/2019 timeframe. The PRISMA tool was used to ensure transparent reporting of the results. Inclusion criteria were: 1) morphologically confirmed epithelial ovarian cancer; 2) recurrent disease within 6 months after completion of platinum-based chemotherapy; 3) treatment with platinum- or non-platinum chemotherapy with agents that are routinely used for OC; 4) no concomitant therapy with targeted or investigational agents or non-platinum doublets; 5) defined response rate (RR) and assessment criteria. Proportion meta-analysis (random-effect model) and beta-regression were conducted to assess the impact of platinum agents on response rate as well as significance of other variables. In the beta-regression model response rate was a dependent variable, while platinum agents (yes or no), used non-platinum drugs and method of response assessment were independent variables. Statistical analysis was dose with meta, metafor and betareg packages of R software. Resultswe identified 7156 articles and screened them for title and abstract, 157 studies for further analysis. Overall, 6327 patients were included in the analysis, efficacy of non-platinum- and platinum-based therapy was assessed in 113 (n = 5272) and 44 (n = 1055) trials respectively. In meta-proportion random-effect model RR among patients treated with platinum-based and non-platinum chemotherapy RR was 36% (95% CI 30-41; I2 = 62%) and 16% (95% CI 14-19; I2=70%) respectively. For sensitivity analysis various regression models were made with different subsets of the trials and additional variables (including year of the trial, percentage of serous subtype of OC and median of prior therapy lines). Platinum was the strongest predictor of response in every developed model. Conclusionthis meta-analysis shows that patients with platinum-resistant ovarian carcinoma may derive significant benefit from reintroduction of platinum agents. These results support recent ESMO-ESGO consensus on treatment of recurrent ovarian cancer.

Venetoclax plus azacitidine (ven/aza) is a new standard of care for adult Acute Myeloid Leukemia (AML) patients who are not candidates for intensive therapies. Risk stratification approaches have been proposed to identify patients with favorable, intermediate, and adverse therapeutic outcomes following ven/aza and other lower intensive therapies. However, most have been developed for retrospective data analyses and have limitations in their application to upfront risk stratification of newly diagnosed patients. Here, we describe an AML risk model, termed the Refined Risk Model (RRM), that is specific for ven/aza, addresses important real-world considerations and utilizes pathology features that have the potential to be available relatively quickly-and-broadly following diagnosis. The RRM was developed and internally validated using a single center cohort of 316 AML patients from the University of Colorado treated upfront with ven/aza, and then externally validated on an AML cohort from a nationwide electronic health record-derived de-identified AML database. The RRM effectively stratified patients into Adverse, Intermediate, and Favorable groups across both the internal and external cohorts; it performed well in subsets with or without allogeneic transplant recipients, demonstrated tolerance to missing data, and showed numerical performance comparable to or exceeding the existing alternatives such as the European Leukemia Network (ELN 2022) and molecular prognostic risk signature (mPRS) models. These findings suggest that the RRM may have potential application in defining the prognostic mortality risk for newly diagnosed AML patients, which may help guide clinical trial design and execution as well as other important elements of AML clinical decision support.

Backgroundintroduction of the poly(ADP-ribose) polymerase (PARP) inhibitors to clinical practice remarkably improved outcomes for advanced epithelial ovarian cancer (EOC) patients. We conducted this study to evaluate efficacy of frontline maintenance olaparib therapy in BRCA-mutated and/or HRD-positive EOC patients in real-world practice setting. Patients and methodswe enrolled patients with FIGO stage III-IV high-grade serous or endometrioid EOC with BRCA1/2 mutations and/or HRD-positive status with complete or partial response to frontline therapy, who were treated in 2014-2024. Main objective of this trial was to compare progression-free survival (PFS) of HRD+/BRCA-mutant advanced EOC patients treated with or without maintenance olaparib in well-balanced treatment arms. Cardinality matching was considered to ensure balancing of the study arms with 1:1 ratio of patients in trial arms. The groups were balanced according to the presence of residual tumor after initial treatment, platinum-free interval duration after frontline therapy, secondary local therapy for recurrent disease, treatment with platinum drugs for relapse and subsequent bevacizumab. The primary endpoint of the study was PFS. Resultscardinality matching with 1:1 ratio resulted in 282 matched patients for the analysis. Groups were well balanced in all baseline characteristics. Median age in both treatment arms was 50 years with no differences in patients age, surgical outcomes, prevalence of BRCA-mutated or HRD-positive disease and response to initial platinum-based therapy. With a median follow up of 37.2 mo. median PFS was 38.0 in the olaparib arm and 13.7 mo. in the control arm, respectively (HR 0.32; 95% CI 0.23-0.43; p<0.001). Estimated 3-year PFS was 50.9% and 11.5%, respectively. Median PFS2 was 49.5 mo. in the olaparib arm compared to 34.3 mo. in the control arm (HR 0.58; 95% CI 0.39-0.85; p=0.005). Conclusionthis study confirms the benefits of olaparib maintenance therapy in patients with HRD- -positive and/or BRCA-mutated advanced EOC in real-world setting. HighlightsO_LIUsing cardinality matching two cohorts of patients after frontline therapy were made (treated with maintenance olaparib vs not); C_LIO_LIMedian PFS was 38.0 in the olaparib arm and 13.7 mo. in the control arm, respectively (HR 0.32; 95% CI 0.23-0.43; p<0.001); C_LIO_LIThis data confirms efficacy of maintenance olaparib for BRCA/HRD-positive advanced epithelial ovarian cancer in routine clinical practice. C_LI

Bleeding in patients with acute myeloid leukemia (AML) receiving intensive induction chemotherapy is multifactorial and contributes to early death. We sought to define incidence and risk factors of grade 4 bleeding to support strategies for risk mitigation. Bleeding events were assessed according to the WHO bleeding assessment scale, which includes grade 4 bleeding as fatal, life-threatening, retinal with visual impairment, or involving the central nervous system. Using multivariable competing-risk regression analysis with grade 4 bleeding as the primary outcome, we identified risk factors in the development cohort (n=341), which were tested in an independent cohort (n=143). Grade 4 bleeding occurred in 5.9% and 9.8% of patients in the development and validation cohort, respectively. Risk factors that were independently associated with grade 4 bleeding included baseline platelet count [&le;]40 x109/L compared with >40 x109/L, and baseline PT-INR >1.5 or >1.3-1.5 compared with [&le;]1.3. These variables were allocated points, which allowed for stratification of patients with low- and high-risk for grade 4 bleeding. Cumulative incidence of grade 4 bleeding at day+60 was significantly higher among patients with high- versus low-risk (development: 31{+/-}7% vs. 2{+/-}1%, P<0.001, validation: 25{+/-}9% vs. 7{+/-}2%, P=0.008). In both cohorts, high bleeding risk was associated with disseminated intravascular coagulation (DIC) and proliferative disease. We developed and validated a simple risk model for grade 4 bleeding, which enables development of rational risk mitigation strategies to improve early mortality of intensive induction treatment. KEY POINTSO_LIRisk factors predicting grade 4 bleeding were consistent with DIC-like coagulopathy, including prolonged PT-INR and thrombocytopenia. C_LIO_LIThe grade 4 bleeding score was externally validated and allows for preventive strategies to improve early mortality in high-risk patients. C_LI

BackgroundTraditional Phase 1 trials often provide important drug development insights, which can be limited by ethical issues, costs, and lengthy timelines. Advancements in AI based simulations offer a potential avenue for mitigating these challenges. The present study used the aiHumanoid platform, specifically the upgraded DeepNEU database v8.1, to design and conduct a virtual Phase 1 trial, to assess the comparative efficacy and toxicity of standard chemotherapy with gemcitabine plus Taxol vs a combination of standard chemotherapy plus COTI-2 for treating Pancreatic Adenocarcinoma (PAC). MethodsApplying the updated DeepNEU database of 7267 genotypic and phenotypic concepts linked through 67491 relationships, the study used aiHumanoid simulations to predict outcomes from 30 virtual patients. Data from the standard chemotherapy arm and the standard treatment plus COTI2 arm were analyzed at 25%, 50%, 75%, and 100% of maximal dose. Estimates of efficacy and potential toxicities were based on a combination of the paired 2 tailed T test and Cohens d values as a true estimate of treatment effects. ResultsThe novel combined treatment regimen, especially at 100% dosage, showed medium to large treatment effects on the entire Pancreatic Adenocarcinoma disease profile. Notably, a significant decrease was observed in all disease profile components, bolstered by p-values less than 8.68E-5 and Cohens d values >=0.335. While evidence hinted at an increased bone marrow toxicity in the novel treatment arm, no individual organoid toxicity exceeded one standard deviation above predicted values. Importantly, COTI-2 treatment demonstrated a dose-dependent increase in p53 levels, significant at p < 0.006. ConclusionThis aiHumanoids virtual Phase 1 trial emphasizes the potential of computational simulations in the drug development process. Our findings indicate a promising treatment pathway combining COTI-2 with standard chemotherapy for Pancreatic Adenocarcinoma. Ongoing development and validation of the aiHumanoid based virtual Phase 1 clinical trial methodology is warranted.

IMPORTANCEImproving the efficiency of interim assessments in phase III trials should reduce trial costs, hasten the approval of efficacious therapies, and mitigate patient exposure to disadvantageous randomizations. OBJECTIVEWe hypothesized that in silico Bayesian early stopping rules improve the efficiency of phase III trials compared with the original frequentist analysis without compromising overall interpretation. DESIGNCross-sectional analysis. SETTING230 randomized phase III oncology trials enrolling 184,752 participants. PARTICIPANTSIndividual patient-level data were manually reconstructed from primary endpoint Kaplan-Meier curves. INTERVENTIONSTrial accruals were simulated 100 times per trial and leveraged published patient outcomes such that only the accrual dynamics, and not the patient outcomes, were randomly varied. MAIN OUTCOMES AND MEASURESEarly stopping was triggered per simulation if interim analysis demonstrated [&ge;] 85% probability of minimum clinically important difference/3 for efficacy or futility. Trial-level early closure was defined by stopping frequencies [&ge;] 0.75. RESULTSA total of 12,451 simulations (54%) met early stopping criteria. Trial-level early stopping frequency was highly predictive of the published outcome (OR, 7.24; posterior probability of association, >99.99%; AUC, 0.91; P < 0.0001). Trial-level early closure was recommended for 82 trials (36%), including 62 trials (76%) which had performed frequentist interim analysis. Bayesian early stopping rules were 96% sensitive (95% CI, 91% to 98%) for detecting trials with a primary endpoint difference, and there was a high level of agreement in overall trial interpretation (Bayesian Cohens {kappa}, 0.95; 95% CrI, 0.92 to 0.99). However, Bayesian interim analysis was associated with >99.99% posterior probability of reducing patient enrollment requirements (P < 0.0001), with an estimated cumulative enrollment reduction of 20,543 patients (11%; 89 patients averaged equally over all studied trials) and an estimated cumulative cost savings of 851 million USD (3.7 million USD averaged equally over all studied trials). CONCLUSIONS AND RELEVANCEBayesian interim analyses may improve randomized trial efficiency by reducing enrollment requirements without compromising trial interpretation. Increased utilization of Bayesian interim analysis has the potential to reduce costs of late-phase trials, reduce patient exposures to ineffective therapies, and accelerate approvals of effective therapies. KEY POINTSO_ST_ABSQuestionC_ST_ABSWhat are the effects of Bayesian early stopping rules on the efficiency of phase III randomized oncology trials? FindingsIndividual-patient level outcomes were reconstructed for 184,752 patients from 230 trials. Compared with the original interim analysis strategy, in silico Bayesian interim analysis reduced patient enrollment requirements and preserved the original trial interpretation. MeaningBayesian interim analysis may improve the efficiency of conducting randomized trials, leading to reduced costs, reduced exposure of patients to disadvantageous treatments, and accelerated approval of efficacious therapies.

A recent randomized clinical trial in non-small cell lung cancer1 confirms what numerous observational studies have reported time of day (ToD) may dramatically influence treatment outcomes in cancer patients. In this recent trial median overall survival (OS) decreased from 28 months in the early ToD arm to 16.8 months in the late ToD arm. We raise the concern that clinical trial outcomes may be influenced by seemingly minor biases in treatment time across arms. We also suggest that by measuring or randomizing treatment-time in clinical trials, we may identify beneficial ToD dependent treatments that would otherwise be overlooked.

Patient-derived xenografts (PDX) and organoids (PDO) are widely used to model cancer and predict treatment response in matched patients. However, their predictive accuracy has not been systematically studied nor compared. We conducted a systematic review and meta-analysis of studies using PDX or PDO from solid tumors treated with identical anti-cancer agents as the matched patient, identifying 411 patient-model pairs (267 PDX, 144 PDO). Overall concordance in treatment response between patients and matched models was 70%, with no significant differences between PDX and PDO. Sensitivity, specificity, positive and negative predictive value were also comparable. Patients whose matched PDO responded to therapy had prolonged progression-free survival. For PDX, this association held only when analyses were restricted to patient-model pairs with low risk of bias after applying a bias assessment metric. Together, these findings suggest that PDO perform similarly to PDX in predicting matched-patient response, while potentially offering lower financial and ethical burdens. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/25333051v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@b635d7org.highwire.dtl.DTLVardef@88ee03org.highwire.dtl.DTLVardef@1c21ed3org.highwire.dtl.DTLVardef@175beef_HPS_FORMAT_FIGEXP M_FIG C_FIG