Prevalence, trends, and characteristics of trials investigating local therapy in contemporary phase 3 clinical cancer research.

BACKGROUND: Although most patients with cancer are treated with local therapy (LT), the proportion of late-phase clinical trials investigating local therapeutic interventions is unknown. The purpose of this study was to determine the proportion, characteristics, and trends of phase 3 cancer clinical trials assessing the therapeutic value of LT over time. METHODS: This was a cross-sectional analysis of interventional randomized controlled trials in oncology published from 2002 through 2020 and registered on ClinicalTrials.gov. Trends and characteristics of LT trials were compared to all other trials. RESULTS: Of 1877 trials screened, 794 trials enrolling 584,347 patients met inclusion criteria. A total of 27 trials (3%) included a primary randomization assessing LT compared with 767 trials (97%) investigating systemic therapy or supportive care. Annual increase in the number of LT trials (slope [m] = 0.28; 95% confidence interval [CI], 0.15-0.39; p < .001) was outpaced by the increase of trials testing systemic therapy or supportive care (m = 7.57; 95% CI, 6.03-9.11; p < .001). LT trials were more often sponsored by cooperative groups (22 of 27 [81%] vs. 211 of 767 [28%]; p < .001) and less often sponsored by industry (5 of 27 [19%] vs. 609 of 767 [79%]; p < .001). LT trials were more likely to use overall survival as primary end point compared to other trials (13 of 27 [48%] vs. 199 of 767 [26%]; p = .01). CONCLUSIONS: In contemporary late-phase oncology research, LT trials are increasingly under-represented, under-funded, and evaluate more challenging end points compared to other modalities. These findings strongly argue for greater resource allocation and funding mechanisms for LT clinical trials. PLAIN LANGUAGE SUMMARY: Most people who have cancer receive treatments directed at the site of their cancer, such as surgery or radiation. We do not know, however, how many trials test surgery or radiation compared to drug treatments (that go all over the body). We reviewed trials testing the most researched strategies (phase 3) completed between 2002 and 2020. Only 27 trials tested local treatments like surgery or radiation compared to 767 trials testing other treatments. Our study has important implications for funding research and understanding cancer research priorities.

Improvement in visual outcomes of patients with base of skull meningioma as a result of evolution in the treatment techniques in the last three decades: a systematic review.

PURPOSE: We systematically reviewed visual outcomes over the last three decades in patients undergoing treatment for base of skull (BOS) meningiomas and provide recommendations to preserve vision. METHODS: In accordance with the PRISMA guidelines for systematic reviews, a search was conducted from 6/1/2022-9/1/2022 using PubMed and Web of Science. Inclusion criteria included (1) patients treated for BOS meningiomas (2) treatment modality specified (3) specifics of surgical techniques and/or dose/fractions of radiotherapy (4) individual patient outcomes of treatment. Each study was assessed for bias based on study design and heterogeneity of results. RESULTS: A total of 50 studies were included (N = 2911). When comparing improved vision versus unchanged or worsened vision, studies investigating surgery alone published from 2006 and onward had significantly better visual outcomes compared to pre-2006 studies (p = 0.02). When comparing improved vision versus unchanged or worsened vision, studies investigating combined therapy with surgery and radiation published from 2008 and onward had significantly better visual outcomes compared to pre-2008 studies (p < 0.01). Combined modality therapy was less likely to worsen vision compared to either surgery or radiation monotherapy (p < 0.01). However, surgery and radiation monotherapy were more likely to actually improve outcomes compared to combination therapy (p < 0.01). CONCLUSION: For over a decade we have observed improvement in visual outcomes in patients managed for meningioma of BOS, likely attributing the innovation in microsurgical and more targeted and conformal radiation techniques. Combination therapy may be the safest option for preventing worsening of vision, but the highest rates of improving visual function are achieved through monotherapy when indicated.

Multi-institution analysis of tumor mutational burden and outcomes in pediatric central nervous system tumor patients.

BACKGROUND: Pediatric central nervous system (CNS) tumors are the leading cause of pediatric cancer mortality. Research addressing genomic biomarkers and clinical outcomes is needed to inform therapeutic decision-making. METHODS: We conducted a retrospective analysis of pediatric patients (age <21) diagnosed with a primary CNS tumor at four upstate New York hospitals from 2008 to 2021. Clinical and histopathologic data were identified from each patient, including genomic analysis of somatic mutations and tumor mutational burden (TMB) where available. These variables were each compared with overall survival using Cox regression analyses. Multivariable analysis was conducted to identify patient characteristics that may independently predict survival. RESULTS: We identified 119 patients. Common tumor types included low-grade glioma (N = 51), high-grade glioma (N = 29), and medulloblastoma (N = 11). Common driver mutations included TP53 inactivation (N = 16), BRAF-KIAA1549 fusion (N = 16), FGFR1 amplification (N = 12), BRAF V600E mutation (N = 12), NF1 loss (N = 12), and H3F3A K28M mutation (N = 6). Median TMB was one mutation/megabase (mut/Mb, range = 0-132). Overall survival was 79.9%. Variables associated with poorer survival on univariable analysis were higher TMB (p = .002, HR 4.97), high-grade tumors (p = .009, HR 84.3), and high-grade glioma histology (p = .021, HR 3.14). Multivariable analyses further identified TMB (p = .011, HR 4.46) and high-grade histology (p = .015, HR 5.28) as independently predictive of worse survival. Tumor progression was more common in high-TMB (N = 15, 44%) than in low-TMB tumors (N = 19, 35%). CONCLUSIONS: High TMB is correlated with higher rates of progression and death as compared to low-TMB tumors. These findings may help identify patients who may benefit from alternative treatments, such as immunotherapies.

Food and Drug Administration approvals in phase 3 Cancer clinical trials.

BACKGROUND: Phase 3 oncologic randomized clinical trials (RCTs) can lead to Food and Drug Administration (FDA) approvals. In this study, we aim to identify trial-related factors associated with trials leading to subsequent FDA drug approvals. METHODS: We performed a database query through the ClinicalTrials.gov registry to search for oncologic phase 3 RCTs on February 2020. We screened all trials for therapeutic, cancer-specific, phase 3, randomized, multi-arm trials. We then identified whether a trial was used for subsequent FDA drug approval through screening of FDA approval announcements. RESULTS: In total, 790 trials were included in our study, with 225 trials (28.4%) generating data that were subsequently used for FDA approvals. Of the 225 FDA approvals identified, 65 (28.9%) were based on trials assessing overall survival (OS) as a primary endpoint (PEP), two (0.9%) were based on trials with a quality of life (QoL) PEP, and 158 approvals (70.2%) were based on trials with other PEP (P = 0.01). FDA approvals were more common among industry funded-trials (219, 97.3%; P < 0.001), and less common among trials sponsored by national cooperative groups (21, 9.3%; P < 0.001). Finally, increased pre-hoc power and meeting patients' accrual target were associated with FDA approvals (P < 0.001). CONCLUSIONS: The majority of FDA approvals are based on data generated from trials analyzing surrogate primary endpoints and trials receiving industry funding. Additional studies are required to understand the complexity of FDA approvals.

Immunotherapy combined with high- and low-dose radiation to all sites leads to complete clearance of disease in a patient with metastatic vaginal melanoma.

A 73-year-old woman with metastatic vaginal mucosal melanoma that had progressed on ipilimumab and nivolumab experienced clinical and radiographic complete response to dual checkpoint inhibitor immunotherapy given in combination with high-dose plus low-dose radiation. General characteristics and treatment options in this disease are highlighted.

Tumor mutational burden and driver mutations: Characterizing the genomic landscape of pediatric brain tumors.

BACKGROUND: Tumor mutational burden (TMB) and driver mutations are potential biomarkers to guide targeted therapy selection. Malignant gliomas with high TMB in children may preferentially benefit from treatment with immune checkpoint inhibitors (ICPIs). Higher TMB may relate to lower incidence of driver mutations, but this relationship has not been studied in pediatric brain tumors. PROCEDURE: Comprehensive genomic profiling was performed on 723 pediatric (≤21 years) brain tumor samples using DNA extracted from formalin-fixed paraffin-embedded tissue. TMB was calculated as mutations per megabase and categorized as low (0-6), intermediate (6-20), or high (>20). Analysis included 80 clinically relevant driver mutations; genomic alterations known to confer a selective growth advantage. RESULTS: Of 723 brain tumors, TMB was low in 91.8%, intermediate in 6.1%, and high in 2.1%. In the high TMB cohort, 93% of tumors harbored a driver mutation; 70% and 63% in the intermediate and low TMB cohorts, respectively (P < 0.05). However, when excluding tumor suppressor genes, high TMB tumors had a decreased incidence of driver mutations (P < 0.001). BRAF alterations were not identified in high TMB tumors, but were enriched in low TMB tumors (P < 0.01). Conversely, there was an association between high TMB tumors and TP53 mutations (P < 10-13 ). Of the 15 tumors with high TMB, 14 were high-grade gliomas and 13 had alterations in TP53. Three homozygous mismatch repair deletions identified were associated with a higher TMB (P < 0.01). CONCLUSIONS: Specific driver mutations appear to have a relationship with TMB. These represent populations in which ICPIs may be more or less effective.

Management and outcomes of primary anorectal melanoma in the United States.

Aims: To analyze outcomes in primary anorectal melanoma, a rare disease with limited data and treatment guidelines. Materials & methods: We analyzed 305 subjects in the National Cancer Database from 2004 to 2015. The primary end point was overall survival (OS). Results: Surgery was predictive of OS (median 2.24 vs 1.18 years; p = 0.009) with no survival difference between local and transabdominal approaches (p = 0.77). No OS benefit was seen with chemotherapy (p = 0.16), radiotherapy (p = 0.31) or adjuvant therapy post surgery (p > 0.05 for all groups). Targeted therapy trended toward higher survival in metastatic patients (1.33 vs 0.55 years; p = 0.06). Conclusion: In nonmetastatic patients, surgery of any method is associated with a survival benefit. The trend for improved survival following targeted therapy in metastatic patients merits further exploration.

Local management of preinvasive and clinical T1-3 penile cancer: utilization of diverse treatment modalities.

Aim: To explore management trends in preinvasive and cT1-T3 penile cancer. Materials & methods: The National Cancer Database was queried (2004-2013) for cT1-T3 M0 penile cancer with specified nonpalliative surgical techniques and histologies (n = 5,728). Results: Local excision (39%) and partial penectomy (38%) were most commonly utilized. Patients with cTis/Ta or cT1 disease more often received nonpenectomy approaches (p < 0.05); cT2-T3 cases more likely underwent penectomy (p < 0.001). No survival differences were observed between penectomy (49.3 months) and nonpenectomy approaches (50.3 months) in the overall cohort (p = 0.107) and when stratifying by T-stage (p > 0.20 for all). Conclusion: This study provides contemporary insight into the landscape for management of this rare disease and can serve as a benchmark for future evaluation of treatment trends.

Bayesian Interim Analysis and Efficiency of Phase III Randomized Trials.

IMPORTANCE: Improving 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. OBJECTIVE: We 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. DESIGN: Cross-sectional analysis. SETTING: 230 randomized phase III oncology trials enrolling 184,752 participants. PARTICIPANTS: Individual patient-level data were manually reconstructed from primary endpoint Kaplan-Meier curves. INTERVENTIONS: Trial 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 MEASURES: Early stopping was triggered per simulation if interim analysis demonstrated ≥ 85% probability of minimum clinically important difference/3 for efficacy or futility. Trial-level early closure was defined by stopping frequencies ≥ 0.75. RESULTS: A 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 Cohen's κ, 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 RELEVANCE: Bayesian 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 POINTS: Question: What are the effects of Bayesian early stopping rules on the efficiency of phase III randomized oncology trials?Findings: Individual-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. Meaning: Bayesian 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.

Proportional Hazards Violations in Phase 3 Cancer Clinical Trials: A Potential Source of Trial Misinterpretation.

BACKGROUND: Survival analyses of novel agents with long-term responders often exhibit differential hazard rates over time. Such proportional hazards violations (PHVs) may reduce the power of the log-rank test and lead to misinterpretation of trial results. We aimed to characterize the incidence and study attributes associated with PHVs in phase 3 oncology trials and assess the utility of restricted mean survival time (RMST) and MaxCombo as additional analyses. METHODS: Clinicaltrials.gov and PubMed were searched to identify 2-arm, randomized, phase 3 superiority-design cancer trials with time-to-event primary endpoints and published results through 2020. Patient-level data were reconstructed from published Kaplan-Meier curves. PHVs were assessed using Schoenfeld residuals. RESULTS: Three hundred fifty-seven Kaplan-Meier comparisons across 341 trials were analyzed, encompassing 292,831 enrolled patients. PHVs were identified in 85/357 (23.8%; 95%CI 19.7%, 28.5%) comparisons. In multivariable analysis, non-OS endpoints (odds ratio [OR] 2.16 [95%CI 1.21, 3.87]; P=.009) were associated with higher odds of PHVs, and immunotherapy comparisons (OR 1.94 [95%CI 0.98, 3.86]; P=.058) were weakly suggestive of higher odds of PHVs. Few trials with PHVs (25/85, 29.4%) pre-specified a statistical plan to account for PHVs. Fourteen trials with PHVs exhibited discordant statistical signals with RMST or MaxCombo, of which ten (71%) reported negative results. CONCLUSION: PHVs are common across therapy types, and attempts to account for PHVs in statistical design are lacking despite the potential for results exhibiting non-proportional hazards to be misinterpreted.

Towards Treatment Effect Interpretability: A Bayesian Re-analysis of 194,129 Patient Outcomes Across 230 Oncology Trials.

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 ≤ 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 ≤ 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.

Secondary Endpoint Utilization and Publication Rate among Phase III Oncology Trials.

Secondary endpoints (SEP) provide crucial information in the interpretation of clinical trials, but their features are not yet well understood. Thus, we sought to empirically characterize the scope and publication rate of SEPs among late-phase oncology trials. We assessed SEPs for each randomized, published phase III oncology trial across all publications and ClinicalTrials.gov, performing logistic regressions to evaluate associations between trial characteristics and SEP publication rates. After screening, a total of 280 trials enrolling 244,576 patients and containing 2,562 SEPs met the inclusion criteria. Only 22% of trials (62/280) listed all SEPs consistently between ClinicalTrials.gov and the trial protocol. The absolute number of SEPs per trial increased over time, and trials sponsored by industry had a greater number of SEPs (median 9 vs. 5 SEPs per trial; P < 0.0001). In total, 69% of SEPs (1,770/2,562) were published. The publication rate significantly varied by SEP category [X2 (5, N = 2,562) = 245.86; P < 0.001]. SEPs that place the most burden on patients, such as patient-reported outcomes and translational correlatives, were published at 63% (246/393) and 44% (39/88), respectively. Trials with more SEPs were associated with lower overall SEP publication rates. Overall, our findings are that SEP publication rates in late-phase oncology trials are highly variable based on the type of SEP. To avoid undue burden on patients and promote transparency of findings, trialists should weigh the biological and clinical relevance of each SEP together with its feasibility at the time of trial design. SIGNIFICANCE: In this investigation, we characterized the utilization and publication rates of SEPs among late-phase oncology trials. Our results draw attention to the proliferation of SEPs in recent years. Although overall publication rates were high, underpublication was detected among endpoints that may increase patient burden (such as translational correlatives and patient-reported outcomes).

Association of differential censoring with survival and suboptimal control arms among oncology clinical trials.

Differential censoring, which refers to censoring imbalance between treatment arms, may bias the interpretation of survival outcomes in clinical trials. In 146 phase III oncology trials with statistically significant time-to-event surrogate primary endpoints, we evaluated the association between differential censoring in the surrogate primary endpoints, control arm adequacy, and the subsequent statistical significance of overall survival results. Twenty-four (16%) trials exhibited differential censoring that favored the control arm, whereas 15 (10%) exhibited differential censoring that favored the experimental arm. Positive overall survival was more common in control arm differential censoring trials (63%) than in trials without differential censoring (37%) or with experimental arm differential censoring (47%; odds ratio = 2.64, 95% confidence interval = 1.10 to 7.20; P = .04). Control arm differential censoring trials more frequently used suboptimal control arms at 46% compared with 20% without differential censoring and 13% with experimental arm differential censoring (odds ratio = 3.60, 95% confidence interval = 1.29 to 10.0; P = .007). The presence of control arm differential censoring in trials with surrogate primary endpoints, especially in those with overall survival conversion, may indicate an inadequate control arm and should be examined and explained.

Prevalence and implications of significance testing for baseline covariate imbalance in randomised cancer clinical trials: The Table 1 Fallacy.

BACKGROUND: The 'Table 1 Fallacy' refers to the unsound use of significance testing for comparing the distributions of baseline variables between randomised groups to draw erroneous conclusions about balance or imbalance. We performed a cross-sectional study of the Table 1 Fallacy in phase III oncology trials. METHODS: From ClinicalTrials.gov, 1877 randomised trials were screened. Multivariable logistic regressions evaluated predictors of the Table 1 Fallacy. RESULTS: A total of 765 randomised controlled trials involving 553,405 patients were analysed. The Table 1 Fallacy was observed in 25% of trials (188 of 765), with 3% of comparisons deemed significant (59 of 2353), approximating the typical 5% type I error assertion probability. Application of trial-level multiplicity corrections reduced the rate of significant findings to 0.3% (six of 2345 tests). Factors associated with lower odds of the Table 1 Fallacy included industry sponsorship (adjusted odds ratio [aOR] 0.29, 95% confidence interval [CI] 0.18-0.47; multiplicity-corrected P < 0.0001), larger trial size (≥795 versus <280 patients; aOR 0.32, 95% CI 0.19-0.53; multiplicity-corrected P = 0.0008), and publication in a European versus American journal (aOR 0.06, 95% CI 0.03-0.13; multiplicity-corrected P < 0.0001). CONCLUSIONS: This study highlights the persistence of the Table 1 Fallacy in contemporary oncology randomised controlled trials, with one of every four trials testing for baseline differences after randomisation. Significance testing is a suboptimal method for identifying unsound randomisation procedures and may encourage misleading inferences. Journal-level enforcement is a possible strategy to help mitigate this fallacy.

Incidence of Primary End Point Changes Among Active Cancer Phase 3 Randomized Clinical Trials.

Importance: Primary end point (PEP) changes to an active clinical trial raise questions regarding trial quality and the risk of outcome reporting bias. It is unknown how the frequency and transparency of the reported changes depend on reporting method and whether the PEP changes are associated with trial positivity (ie, the trial met the prespecified statistical threshold for PEP positivity). Objectives: To assess the frequency of reported PEP changes in oncology randomized clinical trials (RCTs) and whether these changes are associated with trial positivity. Design, Setting, and Participants: This cross-sectional study used publicly available data for complete oncology phase 3 RCTs registered in ClinicalTrials.gov from inception through February 2020. Main Outcomes and Measures: The main outcome was change between the initial PEP and the final reported PEP, assessed using 3 methods: (1) history of tracked changes on ClinicalTrials.gov, (2) self-reported changes noted in the article, and (3) changes reported within the protocol, including all available protocol documents. Logistic regression analyses were performed to evaluate whether PEP changes were associated with US Food and Drug Administration approval or trial positivity. Results: Of 755 included trials, 145 (19.2%) had PEP changes found by at least 1 of the 3 detection methods. Of the 145 trials with PEP changes, 102 (70.3%) did not have PEP changes disclosed within the manuscript. There was significant variability in rates of PEP detection by each method (χ2 = 72.1; P < .001). Across all methods, PEP changes were detected at higher rates when multiple versions of the protocol (47 of 148 [31.8%]) were available compared with 1 version (22 of 134 [16.4%]) or no protocol (76 of 473 [16.1%]) (χ2 = 18.7; P < .001). Multivariable analysis demonstrated that PEP changes were associated with trial positivity (odds ratio, 1.86; 95% CI, 1.25-2.82; P = .003). Conclusions and Relevance: This cross-sectional study revealed substantial rates of PEP changes among active RCTs; PEP changes were markedly underreported in published articles and mostly occurred after reported study completion dates. Significant discrepancies in the rate of detected PEP changes call into question the role of increased protocol transparency and completeness in identifying key changes occurring in active trials.

Inclusion of premenopausal women in breast cancer clinical trials.

BACKGROUND: Patients with premenopausal breast cancer (PMBC) have been historically excluded from some clinical trials because of the limitations of using endocrine therapy (ET) in this population. We analyzed breast cancer randomized clinical trials (RCTs) to determine the rates of and factors associated with inclusion of PMBC patients to provide a benchmark for PMBC inclusion in RCTs moving forward. METHODS: Using ClinicalTrials.Gov, we identified breast cancer phase III RCTs and extracted inclusion criteria and patient enrollment information. Multiple binary logistic regression modeling was used to assess trial-related factors that were associated with PMBC patient inclusion. RESULTS: Of 170 breast cancer RCTs identified, 131 (77.1%) included PMBC patients. Sixty-five (38.2%) trials analyzed patients with hormone-receptor-positive (HR+) and HER2-negative (HER2-) breast cancer, of which 31 (47.7%) allowed for enrollment of PMBC patients. Lower rates of PMBC inclusion were seen in trials that studied HR+/HER2-patients (47.7% PMBC inclusion in HR+/HER2-trials vs. 94.3% in non-HR+/HER2-trials, aOR 0.07 [95% CI: 0.02-0.19], p < 0.001) and in trials that randomized or mandated ET (44.4% in ET trials vs. 83.2% in non-ET trials, aOR 0.21 [95% CI: 0.10-0.83], p = 0.02). Trials studying chemotherapy (CT) were associated with inclusion of PMBC patients (100% in CT trials vs. 70.5% in non-CT trials, a OR 14.02 [95% CI: 1.54-127.91], p = 0.01). All surgical and radiation therapy clinical trials allowed for the inclusion of PMBC patients in their eligibility criteria. CONCLUSIONS: Breast cancer clinical trials should carefully select their enrollment criteria and consider inclusion of premenopausal patients when appropriate.

Association between Prior Malignancy Exclusion Criteria and Age Disparities in Cancer Clinical Trials.

Prior malignancy exclusion criteria (PMEC) are often utilized in cancer clinical trials; however, the incidence of PMEC and the association of PMEC with trial participant age disparities remain poorly understood. This study aimed to identify age disparities in oncologic randomized clinical trials as a result of PMEC. Using a comprehensive collection of modern phase III cancer clinical trials obtained via ClinicalTrials.gov, we assessed the incidence and covariates associated with trials excluding patients with prior cancers within 5+ years from registration (PMEC-5). Using the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database, we further sought to determine the correlation between PMEC-5 and age disparities. PMEC-5 were used in 41% of all trials, with higher PMEC-5 utilization among industry-supported trials as well as trials evaluating a targeted therapy. Comparing trial patient median ages with population-matched median ages by disease site and time-period, we assessed the association between PMEC-5 and age disparities among trial participants. PMEC-5 were independently associated with heightened age disparities, which further worsened with longer exclusionary timeframes. Together, PMEC likely contribute to age disparities, suggesting that eligibility criteria modernization through narrower PMEC timeframes may work toward reducing such disparities in cancer clinical trial enrollment.

High Plus Low Dose Radiation Strategy in Combination with TIGIT and PD1 Blockade to Promote Systemic Antitumor Responses.

Tumors deploy various immune-evasion mechanisms that create a suppressive environment and render effector T-cells exhausted and inactive. Therefore, a rational utilization of checkpoint inhibitors may alleviate exhaustion and may partially restore antitumor functions. However, in high-tumor-burden models, the checkpoint blockade fails to maintain optimal efficacy, and other interventions are necessary to overcome the inhibitory tumor stroma. One such strategy is the use of radiotherapy to reset the tumor microenvironment and maximize systemic antitumor outcomes. In this study, we propose the use of anti-PD1 and anti-TIGIT checkpoint inhibitors in conjunction with our novel RadScopal technique to battle highly metastatic lung adenocarcinoma tumors, bilaterally established in 129Sv/Ev mice, to mimic high-tumor-burden settings. The RadScopal approach is comprised of high-dose radiation directed at primary tumors with low-dose radiation delivered to secondary tumors to improve the outcomes of systemic immunotherapy. Indeed, the triple therapy with RadScopal + anti-TIGIT + anti-PD1 was able to prolong the survival of treated mice and halted the growth of both primary and secondary tumors. Lung metastasis counts were also significantly reduced. In addition, the low-dose radiation component reduced TIGIT receptor (PVR) expression by tumor-associated macrophages and dendritic cells in secondary tumors. Finally, low-dose radiation within triple therapy decreased the percentages of TIGIT+ exhausted T-cells and TIGIT+ regulatory T-cells. Together, our translational approach provides a new treatment alternative for cases refractory to other checkpoints and may bring immunotherapy into a new realm of systemic disease control.

The potential of biology-guided radiation therapy in thoracic cancer: A preliminary treatment planning study.

Purpose: We investigated the feasibility of biology-guided radiotherapy (BgRT), a technique that utilizes real-time positron emission imaging to minimize tumor motion uncertainties, to spare nearby organs at risk. Methods: Volumetric modulated arc therapy (VMAT), intensity-modulated proton (IMPT) therapy, and BgRT plans were created for a paratracheal node recurrence (case 1; 60 Gy in 10 fractions) and a primary peripheral left upper lobe adenocarcinoma (case 2; 50 Gy in four fractions). Results: For case 1, BgRT produced lower bronchus V40 values compared to VMAT and IMPT. For case 2, total lung V20 was lower in the BgRT case compared to VMAT and IMPT. Conclusions: BgRT has the potential to reduce the radiation dose to proximal critical structures but requires further detailed investigation.