The Statistical Significance Revolution.

Statistical significance has long relied on the criterion of p < 0.05. While it has generally functioned well, it has engendered some negative practices to circumvent this threshold and been criticized as too inflexible. We concur with the statisticians and methodologists who are currently arguing for more flexibility to the p-value and more reliance on the 95% confidence interval; this is likely to change future practice in data analysis and interpretation in oncology.

Management of phaeochromocytoma and paraganglioma in patients with germline SDHB pathogenic variants: an international expert Consensus statement.

Adult and paediatric patients with pathogenic variants in the gene encoding succinate dehydrogenase (SDH) subunit B (SDHB) often have locally aggressive, recurrent or metastatic phaeochromocytomas and paragangliomas (PPGLs). Furthermore, SDHB PPGLs have the highest rates of disease-specific morbidity and mortality compared with other hereditary PPGLs. PPGLs with SDHB pathogenic variants are often less differentiated and do not produce substantial amounts of catecholamines (in some patients, they produce only dopamine) compared with other hereditary subtypes, which enables these tumours to grow subclinically for a long time. In addition, SDHB pathogenic variants support tumour growth through high levels of the oncometabolite succinate and other mechanisms related to cancer initiation and progression. As a result, pseudohypoxia and upregulation of genes related to the hypoxia signalling pathway occur, promoting the growth, migration, invasiveness and metastasis of cancer cells. These factors, along with a high rate of metastasis, support early surgical intervention and total resection of PPGLs, regardless of the tumour size. The treatment of metastases is challenging and relies on either local or systemic therapies, or sometimes both. This Consensus statement should help guide clinicians in the diagnosis and management of patients with SDHB PPGLs.

Angiopoietin-2 blockade suppresses growth of liver metastases from pancreatic neuroendocrine tumors by promoting T cell recruitment.

Improving the management of metastasis in pancreatic neuroendocrine tumors (PanNETs) is critical, as nearly half of patients with PanNETs present with liver metastases, and this accounts for the majority of patient mortality. We identified angiopoietin-2 (ANGPT2) as one of the most upregulated angiogenic factors in RNA-Seq data from human PanNET liver metastases and found that higher ANGPT2 expression correlated with poor survival rates. Immunohistochemical staining revealed that ANGPT2 was localized to the endothelial cells of blood vessels in PanNET liver metastases. We observed an association between the upregulation of endothelial ANGPT2 and liver metastatic progression in both patients and transgenic mouse models of PanNETs. In human and mouse PanNET liver metastases, ANGPT2 upregulation coincided with poor T cell infiltration, indicative of an immunosuppressive tumor microenvironment. Notably, both pharmacologic inhibition and genetic deletion of ANGPT2 in PanNET mouse models slowed the growth of PanNET liver metastases. Furthermore, pharmacologic inhibition of ANGPT2 promoted T cell infiltration and activation in liver metastases, improving the survival of mice with metastatic PanNETs. These changes were accompanied by reduced plasma leakage and improved vascular integrity in metastases. Together, these findings suggest that ANGPT2 blockade may be an effective strategy for promoting T cell infiltration and immunostimulatory reprogramming to reduce the growth of liver metastases in PanNETs.

Novel Therapeutic Strategies Exploiting the Unique Properties of Neuroendocrine Neoplasms.

BACKGROUND: Over the last few decades of treatment, the outcomes for at least some subsets of neuroendocrine neoplasms (NENs) have improved. However, the identification of new vulnerabilities for this heterogeneous group of cancers remains a priority. METHODS: Using two libraries of compounds selected for potential repurposing, we identified the inhibitors of nicotinamide phosphoribosyltransferase (NAMPT) and histone deacetylases (HDAC) as the agents with the highest activity. We validated the hits in an expanded set of neuroendocrine cell lines and examined the mechanisms of action. RESULTS: In Kelly, NH-6, and NCI-H82, which are two neuroblastoma and one small cell lung cancer cell lines, respectively, metabolic studies suggested that cell death following NAMPT inhibition is the result of a reduction in basal oxidative phosphorylation and energy production. NAMPT is the rate-limiting enzyme in the production of NAD+, and in the three cell lines, NAMPT inhibition led to a marked reduction in the ATP and NAD+ levels and the catalytic activity of the citric acid cycle. Moreover, comparative analysis of the mRNA expression in drug-sensitive and -insensitive cell lines found less dependency of the latter on oxidative phosphorylation for their energy requirement. Further, the analysis of HDAC and NAMPT inhibitors administered in combination found marked activity using low sub-lethal concentrations of both agents, suggesting a synergistic effect. CONCLUSION: These data suggest NAMPT inhibitors alone or in combination with HDAC inhibitors could be particularly effective in the treatment of neuroendocrine neoplasms.

Ethnic diversity in treatment response for colorectal cancer: proof of concept for radiomics-driven enrichment trials.

BACKGROUND: Several barriers hamper recruitment of diverse patient populations in multicenter clinical trials which determine efficacy of new systemic cancer therapies. PURPOSE: We assessed if quantitative analysis of computed tomography (CT) scans of metastatic colorectal cancer (mCRC) patients using imaging features that predict overall survival (OS) can unravel the association between ethnicity and efficacy. METHODS: We retrospectively analyzed CT images from 1584 mCRC patients in two phase III trials evaluating FOLFOX ± panitumumab (n = 331, 350) and FOLFIRI ± aflibercept (n = 437, 466) collected from August 2006 to March 2013. Primary and secondary endpoints compared RECIST1.1 response at month-2 and delta tumor volume at month-2, respectively. An ancillary study compared imaging phenotype using a peer-reviewed radiomics-signature combining 3 imaging features to predict OS landmarked from month-2. Analysis was stratified by ethnicity. RESULTS: In total, 1584 patients were included (mean age, 60.25 ± 10.57 years; 969 men). Ethnicity was as follows: African (n = 50, 3.2%), Asian (n = 66, 4.2%), Caucasian (n = 1413, 89.2%), Latino (n = 27, 1.7%), Other (n = 28, 1.8%). Overall baseline tumor volume demonstrated Africans and Caucasians had more advanced disease (p < 0.001). Ethnicity was associated with treatment response. Response per RECIST1.1 at month-2 was distinct between ethnicities (p = 0.048) with higher response rate (55.6%) in Latinos. Overall delta tumor volume at month-2 demonstrated that Latino patients more likely experienced response to treatment (p = 0.021). Radiomics phenotype was also distinct in terms of tumor radiomics heterogeneity (p = 0.023). CONCLUSION: This study highlights how clinical trials that inadequately represent minority groups may impact associated translational work. In appropriately powered studies, radiomics features may allow us to unravel associations between ethnicity and treatment efficacy, better elucidate mechanisms of resistance, and promote diversity in trials through predictive enrichment. CLINICAL RELEVANCE STATEMENT: Radiomics could promote clinical trial diversity through predictive enrichment, hence benefit to historically underrepresented racial/ethnic groups that may respond variably to treatment due to socioeconomic factors and built environment, collectively referred to as social determinants of health. KEY POINTS: •Findings indicate ethnicity was associated with treatment response across all 3 endpoints. First, response per RECIST1.1 at month-2 was distinct between ethnicities (p = 0.048) with higher response rate (55.6%) in Latinos. •Second, the overall delta tumor volume at month-2 demonstrated that Latino patients were more likely to experience response to treatment (p = 0.021). Radiomics phenotype was also distinct in terms of tumor radiomics heterogeneity (p = 0.023).

Baseline Radiomic Signature to Estimate Overall Survival in Patients With NSCLC.

INTRODUCTION: We aimed to define a baseline radiomic signature associated with overall survival (OS) using baseline computed tomography (CT) images obtained from patients with NSCLC treated with nivolumab or chemotherapy. METHODS: The radiomic signature was developed in patients with NSCLC treated with nivolumab in CheckMate-017, -026, and -063. Nivolumab-treated patients were pooled and randomized to training, calibration, or validation sets using a 2:1:1 ratio. From baseline CT images, volume of tumor lesions was semiautomatically segmented, and 38 radiomic variables depicting tumor phenotype were extracted. Association between the radiomic signature and OS was assessed in the nivolumab-treated (validation set) and chemotherapy-treated (test set) patients in these studies. RESULTS: A baseline radiomic signature was identified using CT images obtained from 758 patients. The radiomic signature used a combination of imaging variables (spatial correlation, tumor volume in the liver, and tumor volume in the mediastinal lymph nodes) to output a continuous value, ranging from 0 to 1 (from most to least favorable estimated OS). Given a threshold of 0.55, the sensitivity and specificity of the radiomic signature for predicting 3-month OS were 86% and 77.8%, respectively. The signature was identified in the training set of patients treated with nivolumab and was significantly associated (p < 0.0001) with OS in patients treated with nivolumab or chemotherapy. CONCLUSIONS: The radiomic signature provides an early readout of the anticipated OS in patients with NSCLC treated with nivolumab or chemotherapy. This could provide important prognostic information and may support risk stratification in clinical trials.

Tumor Growth Rate Informs Treatment Efficacy in Metastatic Pancreatic Adenocarcinoma: Application of a Growth and Regression Model to Pivotal Trial and Real-World Data.

BACKGROUND: Methods for screening agents earlier in development and strategies for conducting smaller randomized controlled trials (RCTs) are needed. METHODS: We retrospectively applied a tumor growth model to estimate the rates of growth of pancreatic cancer using radiographic tumor measurements or serum CA 19-9 values from 3033 patients with stages III-IV PDAC who were enrolled in 8 clinical trials or were included in 2 large real-world data sets. RESULTS: g correlated inversely with OS and was consistently lower in the experimental arms than in the control arms of RCTs. At the individual patient level, g was significantly faster for lesions metastatic to the liver relative to those localized to the pancreas. Regardless of regimen, g increased toward the end of therapy, often by over 3-fold. CONCLUSIONS: Growth rates of PDAC can be determined using radiographic tumor measurement and CA 19-9 values. g is inversely associated with OS and can differentiate therapies within the same trial and across trials. g can also be used to characterize changes in the behavior of an individual's PDAC, such as differences in the growth rate of lesions based on metastatic site, and the emergence of chemoresistance. We provide examples of how g can be used to benchmark phase II and III clinical data to a virtual reference arm to inform go/no go decisions and consider novel trial designs to optimize and accelerate drug development.

Influence of Cancer on COVID-19 Incidence, Outcomes, and Vaccine Effectiveness: A Prospective Cohort Study of U.S. Veterans.

PURPOSE: Coronavirus disease 2019 (COVID-19) has been a constant health threat since its emergence. Amongst risk factors proposed, a diagnosis of cancer has been worrisome. We report the impact of cancer and other risk factors in US Veterans receiving care at Veterans Administration (VA) Hospitals, their adjusted odds ratio (aOR) for infection and death, and report on the impact of vaccines on the incidence and severity of COVID-19 infections in Veterans without/with cancer. METHODS: We conducted a cohort study of US Veterans without/with cancer by mining VA COVID-19 Shared Data Resource (CSDR) data using the VA Informatics and Computing Infrastructure (VINCI). Our observation period includes index dates from 14DEC2020 to 25JAN2022, encompassing both the delta and omicron waves in the US. RESULTS: We identified 915,928 Veterans, 24% of whom were African Americans who had undergone COVID testing-688,541 were and 227,387 were not vaccinated. 157,072 had a cancer diagnosis in the preceding two years. Age emerged as the major risk factor, with gender, BMI, and (Elixhauser) comorbidity contributing less. Among veterans with solid tumors other than lung cancer, risks of infection and death within 60 days were comparable to Veterans without cancer. However, those with hematologic malignancies fared worse. Vaccination was highly effective across all cancer cohorts; the respective rates of infection and death after infection were 8% and 5% among the vaccinated compared to 47% and 10% in the unvaccinated. Amongst vaccinated, increased risk of infection was noted in both, Veterans with hematologic malignancy treated with chemotherapy (HR, 2.993, P < 0.0001) or targeted therapies (HR, 1.781, P < 0.0001), and in solid tumors treated with either chemotherapy (HR 2.328, 95%CI 2.075-2.611, P < 0.0001) or targeted therapies (HR 1.328, P < 0.0001) when compared to those not on treatment. CONCLUSIONS: Risk for COVID-19 infection and death from infection vary based on cancer type and therapies administered. Importantly and encouragingly, the duration of protection from infection following vaccination in Veterans with a diagnosis of cancer was remarkably like those without a cancer diagnosis. Veterans with hematologic malignancies are especially vulnerable, with lower vaccine effectiveness (VE).

Novel biomarkers in NSCLC: Radiomic analysis, kinetic analysis, and circulating tumor DNA.

Current radiographic methods of measuring treatment response for patients with nonsmall cell lung cancer have significant limitations. Recently, new modalities using standard of care images or minimally invasive blood-based DNA tests have gained interest as methods of evaluating treatment response. This article highlights three emerging modalities: radiomic analysis, kinetic analysis and serum-based measurement of circulating tumor DNA, with a focus on the clinical evidence supporting these methods. Additionally, we discuss the possibility of combining these modalities to develop a robust biomarker with strong correlation to clinically meaningful outcomes that could impact clinical trial design and patient care. At Last, we focus on how these methods specifically apply to a Veteran population.

Early Readout on Overall Survival of Patients With Melanoma Treated With Immunotherapy Using a Novel Imaging Analysis.

IMPORTANCE: Existing criteria to estimate the benefit of a therapy in patients with cancer rely almost exclusively on tumor size, an approach that was not designed to estimate survival benefit and is challenged by the unique properties of immunotherapy. More accurate prediction of survival by treatment could enhance treatment decisions. OBJECTIVE: To validate, using radiomics and machine learning, the performance of a signature of quantitative computed tomography (CT) imaging features for estimating overall survival (OS) in patients with advanced melanoma treated with immunotherapy. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study used radiomics and machine learning to retrospectively analyze CT images obtained at baseline and first follow-up and their associated clinical metadata. Data were prospectively collected in the KEYNOTE-002 (Study of Pembrolizumab [MK-3475] Versus Chemotherapy in Participants With Advanced Melanoma; 2017 analysis) and KEYNOTE-006 (Study to Evaluate the Safety and Efficacy of Two Different Dosing Schedules of Pembrolizumab [MK-3475] Compared to Ipilimumab in Participants With Advanced Melanoma; 2016 analysis) multicenter clinical trials. Participants included 575 patients with a diagnosis of advanced melanoma who were randomly assigned to training and validation sets. Data for the present study were collected from November 20, 2012, to June 3, 2019, and analyzed from July 1, 2019, to September 15, 2021. INTERVENTIONS: KEYNOTE-002 featured trial groups testing intravenous pembrolizumab, 2 mg/kg or 10 mg/kg every 2 or every 3 weeks based on randomization, or investigator-choice chemotherapy; KEYNOTE-006 featured trial groups testing intravenous ipilimumab, 3 mg/kg every 3 weeks and intravenous pembrolizumab, 10 mg/kg every 2 or 3 weeks based on randomization. MAIN OUTCOMES AND MEASURES: The performance of the signature CT imaging features for estimating OS at the month 6 posttreatment landmark in patients who received pembrolizumab was measured using an area under the time-dependent receiver operating characteristics curve (AUC). RESULTS: A random forest model combined 25 imaging features extracted from tumors segmented on CT images to identify the combination (signature) that best estimated OS with pembrolizumab in 575 patients. The signature combined 4 imaging features, 2 related to tumor size and 2 reflecting changes in tumor imaging phenotype. In the validation set (287 patients treated with pembrolizumab), the signature reached an AUC for estimation of OS status of 0.92 (95% CI, 0.89-0.95). The standard method, Response Evaluation Criteria in Solid Tumors 1.1, achieved an AUC of 0.80 (95% CI, 0.75-0.84) and classified tumor outcomes as partial or complete response (93 of 287 [32.4%]), stable disease (90 of 287 [31.3%]), or progressive disease (104 of 287 [36.2%]). CONCLUSIONS AND RELEVANCE: The findings of this prognostic study suggest that the radiomic signature discerned from conventional CT images at baseline and on first follow-up may be used in clinical settings to provide an accurate early readout of future OS probability in patients with melanoma treated with single-agent programmed cell death 1 blockade.

An imaging signature to predict outcome in metastatic colorectal cancer using routine computed tomography scans.

BACKGROUND & AIMS: Quantitative analysis of computed tomography (CT) scans of patients with metastatic colorectal cancer (mCRC) can identify imaging signatures that predict overall survival (OS). METHODS: We retrospectively analysed CT images from 1584 mCRC patients on two phase III trials evaluating FOLFOX ± panitumumab (n = 331, 350) and FOLFIRI ± aflibercept (n = 437, 466). In the training set (n = 720), an algorithm was trained to predict OS landmarked from month 2; the output was a signature value on a scale from 0 to 1 (most to least favourable predicted OS). In the validation set (n = 864), hazard ratios (HRs) evaluated the association of the signature with OS using RECIST1.1 as a benchmark of comparison. RESULTS: In the training set, the selected signature combined three features - change in tumour volume, change in tumour spatial heterogeneity, and tumour volume - to predict OS. In the validation set, RECIST1.1 classified patients in three categories: response (n = 166, 19.2%), stable disease (n = 636, 73.6%), and progression (n = 62, 7.2%). The HR was 3.93 (2.79-5.54). Using the same distribution for the signature, the HR was 21.04 (14.88-30.58), showing an incremental prognostic separation. Stable disease by RECIST1.1 was reclassified by the signature along a continuum where patients belonging to the most and least favourable signature quartiles had a median OS of 40.73 (28.49 to NA) months (n = 94) and 7.03 (5.66-7.89) months (n = 166), respectively. CONCLUSIONS: A signature combining three imaging features provides early prognostic information that can improve treatment decisions for individual patients and clinical trial analyses.

Design of placebo-controlled randomized trials of anticancer agents: Ethical considerations based on a review of published trials.

BACKGROUND: Limited information exists about the design of placebo-controlled cancer trials. Through a systematic review of trials published in 2013, we describe placebo use in randomized trials testing anticancer agents and analyze strategies that increase exposure to the experimental regimen. METHODS: Trials were classified as add-on (placebo in combination with standard treatment) or placebo-only. Strategies to allow more than half of the participants to receive the experimental regimen were reviewed. The risk-benefit ratio of receiving the experimental agent was considered favorable if the difference in primary outcome was significant (p ≤ 0.05), neutral if there was no significant difference in the primary outcome and the experimental agent did not add substantial toxicity, and unfavorable otherwise. RESULTS: Eighty trials were included (32,694 participants). Most trials were add-on (69%). The risk-benefit outcome was favorable, neutral, and unfavorable to the experimental agent in 52%, 32%, and 16% of placebo-only trials and 25%, 53%, and 22%, respectively, of add-on trials. Four strategies increased exposure to the experimental regimen: one-way crossover (23%), uneven randomization (21%), three-arms (13%), and randomized discontinuation design (4%); these strategies were used more often in placebo-only trials. CONCLUSION: A minority of participants received placebo alone and strategies to increase experimental exposure were used commonly. Fewer than half of the studies had favorable outcomes, thus defending the use of placebo controls, when there is no established treatment. Strategies that increase patient exposure to experimental agents rather than placebo may expose them to non-beneficial, sometimes toxic, experimental agents.