Sequential Monitoring Procedure Research Articles

Online Monitoring of Test‐Taking Behavior Based on Item Responses and Response Times

AbstractThe study presents multivariate sequential monitoring procedures for examining test‐taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test‐taking behavior. The study in particular proposes three schemes to track different indicators of a test‐taking mode—the observable manifest variables, latent trait variables, and measurement likelihood. For each procedure, sequential sampling strategies are presented to implement online monitoring. Numerical experimentation based on simulated data suggests that the proposed procedures demonstrate adequate performance. The procedures identified examinees with aberrant behaviors with high detection power and timeliness, while maintaining error rates reasonably small. Experimental application to real data also suggested that the procedures have practical relevance to real assessments. Based on the observations from the experiential analysis, the study discusses implications and guidelines for practical use.

Abstract OT2-16-01: ONCX-NAV-G201: A phase 2, basket study of navicixizumab monotherapy or in combination with chemotherapy in patients with select advanced solid tumors: Triple-negative breast cancer cohort (trial in progress)

Abstract Objective: The objective of this Phase 2, open-label, multicenter study is to investigate the antitumor activity of navicixizumab monotherapy or in combination with chemotherapy in patients with advanced solid tumors. Cohort C will enroll triple-negative breast cancer (TNBC) patients. Background: Navicixizumab is a bispecific humanized monoclonal immunoglobulin G2 kappa antibody directed against human delta-like ligand 4, a critical ligand of the NOTCH pathway, and human vascular endothelial growth factor (VEGF). Aberrant NOTCH signaling is associated with chemotherapy resistance, tumor plasticity, enhanced metastatic potential, promotion of a cancer stem cell phenotype, and immune evasion. In TNBC, aberrant NOTCH expression is associated with poor prognosis, making targeting of this pathway an attractive therapeutic strategy. Additionally, NOTCH may mediate resistance to angiogenesis inhibition. While VEGF inhibitors are approved for the treatment of multiple solid tumors, observed anti-tumor activity is limited in breast cancer. Pre-clinical data show that co-inhibition of NOTCH and angiogenesis have superior antitumor activity compared to individual pathway targeting. We postulate that navicixizumab will demonstrate anticancer efficacy against TNBC. Methods: Eligible TNBC patients will have locally advanced or metastatic disease and have received at least 2 and no more than 4 prior lines of standard therapy for metastatic disease, including immunotherapy (for PD-L1 positive TNBC patients), and sacituzumab govitecan. TNBC is defined as ER and PR < 1%, and HER2-negative (IHC 0, 1+, or 2+ and negative fluorescence in situ hybridization [FISH]). Formalin-fixed paraffin-embedded tissue from an archival or a core tumor sample must be available for biomarker analysis. Samples will be tested using Oncomap™ ExTra with the Xerna TME Panel™ to classify patient samples into one of four tumor microenvironment (TME) subtypes based on angiogenic and immune gene expression signatures. Up to 30 patients will be enrolled to each TNBC cohort from approximately 8 sites in the US and will receive 3 mg/kg navicixizumab alone (Cohort C1) or in combination with paclitaxel (80 mg/m2 on Days 1, 8, and 15 of a 28-day cycle) (Cohort C2). Patients will have radiologic tumor assessments every 8 weeks and will continue to receive treatment until disease progression per RECIST v1.1 (as assessed by the investigator), unacceptable toxicity, withdrawal of consent, another protocol-defined discontinuation criterion is met, or the sponsor terminates the study, whichever occurs first. The primary endpoints of the study are objective response rate (ORR) and progression-free survival (PFS). The historical benchmarks for this patient population are estimated at an ORR of < 5% and a 20% PFS rate at 4 months, with targets of 15% and 40% respectively considered promising for this study. Interim efficacy assessments will be at 10-patient increments following the time patients have had at least 1 post-baseline scan. Cohort continuation and future evaluation decisions will be guided by the boundaries identified by a sequential monitoring procedure. Secondary efficacy endpoints include overall survival, time to response, disease control rate, duration of response, and the relationship between antitumor activity of navicixizumab and Xerna TME Panel™ biomarker subtypes. Citation Format: Amelia B. Zelnak, Heinz-Josef Lenz, Kerry Culm, Lukas Makris, Valerie Chamberlain Santos, Hagop Youssoufian, Colleen Mockbee, Kathy D. Miller. ONCX-NAV-G201: A phase 2, basket study of navicixizumab monotherapy or in combination with chemotherapy in patients with select advanced solid tumors: Triple-negative breast cancer cohort (trial in progress) [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr OT2-16-01.

ONCX-NAV-G201: A phase 2 basket study of navicixizumab monotherapy or in combination with chemotherapy in patients with select advanced solid tumors—Colorectal Cancer Cohort (trial in progress).

TPS263 Background: The objective of this Phase 2, open-label, multicenter study is to investigate the antitumor activity of navicixizumab monotherapy or in combination with chemotherapy in patients with advanced solid tumors (NCT05453825). Cohort A will enroll colorectal cancer (CRC) patients. Navicixizumab is a bispecific humanized monoclonal immunoglobulin G2 kappa antibody directed against human delta-like ligand 4, a critical ligand of the NOTCH pathway, and human vascular endothelial growth factor (VEGF). Aggressive CRC remains difficult to treat owing to the aberrant activation of oncogenic signaling pathways including the NOTCH pathway. Preclinical data show that co-inhibition of NOTCH and angiogenesis have superior antitumor activity compared to individual pathway inhibition. We postulate that navicixizumab will demonstrate anticancer efficacy against CRC. Methods: Eligible CRC patients will have locally advanced or metastatic disease and have received at least 2 and no more than 3 prior lines of standard therapy for metastatic disease, including an anti-VEGF monoclonal antibody. Formalin-fixed paraffin-embedded tissue from an archival or a core tumor sample must be available for biomarker analysis. Samples will be tested using Oncomap ExTra with the Xerna TME Panel where patient samples will be classified into one of four tumor microenviroment (TME) subtypes based on angiogenic and immune gene expression signatures. Up to 30 patients will be enrolled to each CRC cohort from approximately 8 sites in the US and will receive 3 mg/kg navicixizumab alone (Cohort A1) or in combination with irinotecan (180 mg/m2 on Days 1 and 15 of a 28-day cycle, Cohort A2). Patients will have radiologic tumor assessments every 8 weeks and will continue to receive treatment until disease progression per RECIST v1.1 (as assessed by the investigator), unacceptable toxicity, withdrawal of consent, another protocol-defined discontinuation criterion is met, or the sponsor terminates the study, whichever occurs first. The primary endpoints of the study are objective response rate (ORR) and progression-free survival (PFS). The historical benchmarks for this patient population are estimated at an ORR of <5% and a 25% PFS rate at 4 months, with targets of 15% and 50% respectively considered promising for this study. Interim efficacy assessments will be at 10-patient increments following the time patients have had at least 1 post-baseline scan. Cohort continuation and future evaluation decisions will be guided by the boundaries identified by a sequential monitoring procedure. Secondary efficacy endpoints include overall survival, time to response, disease control rate, duration of response, and the relationship between antitumor activity of navicixizumab and Xerna TME Panel biomarker subtypes. Clinical trial information: NCT05453825 .

A structured framework for adaptively incorporating external evidence in sequentially monitored clinical trials

ABSTRACT We present a Bayesian framework for sequential monitoring that allows for use of external data, and that can be applied in a wide range of clinical trial applications. The basis for this framework is the idea that, in many cases, specification of priors used for sequential monitoring and the stopping criteria can be semi-algorithmic byproducts of the trial hypotheses and relevant external data, simplifying the process of prior elicitation. Monitoring priors are defined using the family of generalized normal distributions, which comprise a flexible class of priors, naturally allowing one to construct a prior that is peaked or flat about the parameter values thought to be most likely. External data are incorporated into the monitoring process through mixing an a priori skeptical prior with an enthusiastic prior using a weight that can be fixed or adaptively estimated. In particular, we introduce an adaptive monitoring prior for efficacy evaluation that dynamically weighs skeptical and enthusiastic prior components based on the degree to which observed data are consistent with an enthusiastic perspective. The proposed approach allows for prospective and pre-specified use of external data in the monitoring procedure. We illustrate the method for both single-arm and two-arm randomized controlled trials. For the latter case, we also include a retrospective analysis of actual trial data using the proposed adaptive sequential monitoring procedure. Both examples are motivated by completed pediatric trials, and the designs incorporate information from adult trials to varying degrees. Preposterior analysis and frequentist operating characteristics of each trial design are discussed.

Modeling the patient mix for risk-adjusted CUSUM charts.

The improvement of surgical quality and the corresponding early detection of its changes is of increasing importance. To this end, sequential monitoring procedures such as the risk-adjusted CUmulative SUM chart are frequently applied. The patient risk score population (patient mix), which considers the patients’ perioperative risk, is a core component for this type of quality control chart. Consequently, it is important to be able to adapt different shapes of patient mixes and determine their impact on the monitoring scheme. This article proposes a framework for modeling the patient mix by a discrete beta-binomial and a continuous beta distribution for risk-adjusted CUSUM charts. Since the model-based approach is not limited by data availability, any patient mix can be analyzed. We examine the effects on the control chart’s false alarm behavior for more than 100,000 different scenarios for a cardiac surgery data set. Our study finds a negative relationship between the average risk score and the number of false alarms. The results indicate that a changing patient mix has a considerable impact and, in some cases, almost doubles the number of expected false alarms.

Searching for safe-haven assets during the COVID-19 pandemic

The ongoing COVID-19 pandemic has shaken the global financial system and caused great turmoil. Facing unprecedented risks in the markets, people have increasing needs to find a safe haven for their investments. Given that the nature of this crisis is a combination of multiple problems, it is substantially different from all other financial crises known to us. It is therefore urgent to re-evaluate the safe-haven role of some traditional asset types, namely, gold, cryptocurrency, foreign exchange and commodities. This paper introduces a sequential monitoring procedure to detect changes in the left-quantiles of asset returns, and to assess whether a tail change in the equity index can be offset by introducing a safe-haven asset into a simple mean-variance portfolio. The sample studied covers a training period between August–December 2019 and a testing period of December 2019–March 2020. Furthermore, we calculate the cross-quantilogram between pair-wise asset returns and compare their directional predictability on left-quantiles in both normal market conditions and the COVID-19 period. The main results show that the role of safe haven becomes less effective for most of the assets considered in this paper, while gold and soybean commodity futures remain robust as safe-haven assets during this pandemic.

Searching for Safe-haven Assets During the COVID-19 Pandemic

The ongoing COVID-19 pandemic has shaken the global financial system and caused great turmoil. Facing unprecedented risks in the markets, people have increasing needs to find a safe haven for their investments. Given that the nature of this crisis is a combination of multiple problems, it is substantially different from all other financial crises known to us. It is therefore urgent to re-evaluate the safe-haven role of some traditional asset types, namely, gold, cryptocurrency, foreign exchange and commodities. This paper introduces a sequential monitoring procedure to detect changes in the left-quantiles of asset returns, and to assess whether a tail change in the equity index can be offset by introducing a safe-haven asset into a simple mean-variance portfolio. The sample studied covers a training period between August-December 2019 and a testing period of December 2019-March 2020. Furthermore, we calculate the cross-quantilogram between pair-wise asset returns and compare their directional predictability on left-quantiles in both normal market conditions and the COVID-19 period. The main results show that the role of safe haven becomes less effective for most of the assets considered in this paper, while gold and soybean commodity futures remain robust as safe-haven assets during this pandemic.

Nonparametric group sequential methods for recurrent and terminal events from multiple follow-up windows.

Few methods are currently available for group sequential analysis of recurrent events data subject to a terminal event in the clinical trial setting. This research helps fill this gap by developing a completely nonparametric group sequential monitoring procedure for use with the two-sample Tayob and Murray statistic. Advantages of the Tayob and Murray statistic include high power to detect treatment differences when there is correlation between recurrent event times or between recurrent and terminal events in an individual. This statistic does not suffer bias from dependent censoring, regardless of the correlation between event times in an individual. This manuscript briefly reviews the Tayob and Murray statistic, develops and describes how to use methods for its group sequential analysis, and through simulation, compares its operating characteristics with those of Cook and Lawless, which is currently in use as the only available nonparametric method for group sequential analysis of recurrent event data. The merits of our proposed approach are most clearly demonstrated when gap times between recurrent events are correlated; when gap times between events are independent, the Cook and Lawless method is difficult to beat. Simulations demonstrate that as correlation between recurrent event times grows, the reduction in power using the Cook and Lawless approach is substantial when compared to our method. Finally, we use our method to analyze recurrent acute exacerbation outcomes from the azithromycin in chronic obstructive pulmonary disease trial.

Statistical Inferences for Realized Portfolio Weights

Statistical inferences for weights of the global minimum variance portfolio (GMVP) are of both theoretical and practical relevance for mean-variance portfolio selection. Daily realized GMVP weights depend only on realized covariance matrix computed from intraday highfrequency returns. In this paper we deduce both finite sample and asymptotic distributional properties of the realized GMVP weights. Then we develop statistical tests for the GMVP proportions and elaborate sequential monitoring procedures for on-line decisions whether a given portfolio composition deviates from the current GMVP significantly. Our theoretical results are illustrated both in Monte Carlo simulations and in an empirical application.

Editor’s special invited paper: On the efficient score vector in sequential monitoring

ABSTRACTThe use of the efficient score statistic in sequential monitoring procedures is reviewed and analysed. Various models that arise in applications are considered. The efficient score vector has the same optimality property as the generalized likelihood ratio, but it has a simple-structure requiring fewer estimations, and this is especially important when the data have a complicated structure. Furthermore, with the efficient score vector it is possible to detect which component of the parameter vector is different from the hypothetical or the historical value. The problems we solve here were the subjects of separate publications, but with the new methodology they are easily calculated examples.

Monitoring Test for Stability of Dependence Structure in Multivariate Data Based on Copula

In this paper, we consider a sequential monitoring procedure for detecting changes in copula function. We propose a cusum type of monitoring test based on the empirical copula function and apply it to the detection of the distributional changes in copula function. We investigate the asymptotic properties of the stopping time and show that under regularity conditions, its limiting null distribution is the same as the sup of Kiefer process. Moreover, we utilize the bootstrap method in order to obtain the limiting distribution. A simulation study and a real data analysis are conducted to evaluate our test.

Sequential monitoring of the tail behavior of dependent data

We construct a sequential monitoring procedure for changes in the tail index and extreme quantiles of β-mixing random variables, which can be based on a large class of tail index estimators. The assumptions on the data are general enough to be satisfied in a wide range of applications. In a simulation study empirical sizes and power of the proposed tests are studied for linear and non-linear time series. Finally, we use our results to monitor Bank of America stock log-losses from 2007 to 2012 and detect changes in extreme quantiles without an accompanying detection of a tail index break.

Sequential Monitoring for Changes in Models with a Polynomial Trend

This article considers, for the first time, sequential monitoring procedures that detect possible parameter changes in the polynomial trend models. A new class of sequential monitoring procedures that based on generalized fluctuation testing principle is proposed. The asymptotic null distributions and the consistency of the proposed tests are derived and their asymptotic critical values are tabulated. The methods are illustrated and compared in a small simulation study. In particular, we apply the proposed tests to investigate the Chinese commodity retail sales and consumer price indexes. Simulations and applications support our method.

Dependent functional linear models with applications to monitoring structural change

We study sequential monitoring procedures that detect instabilities of the regression operator in an underlying (fully) functional regression model allowing for dependence. These open-end and closed-end procedures are built on a functional principal components analysis of both the predictor and response functions, thus giving rise to multivariate detector functions, whose fluctuations are compared against a curved threshold function. The main theoretical result of the paper quantifies the large-sample behavior of the procedures under the null hypothesis of a stable regression operator. To establish these limit results, classical results on functional principal components analysis are generalized to a dependent setting, which may be of interest in its own sake. In an accompanying empirical study we illustrate the finite sample properties, while an application to environmental data highlights practical usefulness. To the best of our knowledge this is the first paper that combines sequential with functional data methodology.

SEQUENTIAL TESTING FOR THE STABILITY OF HIGH-FREQUENCY PORTFOLIO BETAS

Despite substantial criticism, variants of the capital asset pricing model (CAPM) remain to this day the primary statistical tools for portfolio managers to assess the performance of financial assets. In the CAPM, the risk of an asset is expressed through its correlation with the market, widely known as the beta. There is now a general consensus among economists that these portfolio betas are time-varying and that, consequently, any appropriate analysis has to take this variability into account. Recent advances in data acquisition and processing techniques have led to an increased research output concerning high-frequency models. Within this framework, we introduce here a modified functional CAPM and sequential monitoring procedures to test for the constancy of the portfolio betas. As our main results we derive the large-sample properties of these monitoring procedures. In a simulation study and an application to S&P 100 data we show that our method performs well in finite samples.

Sequential testing of gradual changes in the drift of a stochastic process

In this paper, some sequential monitoring procedures are constructed and analyzed for detecting a “gradual” change in the drift parameter of a general stochastic process satisfying a certain (weak) invariance principle. It is shown that the tests can be constructed such that the “false alarm rate” attains a prescribed level (say) α and that the tests have “asymptotic power 1”. A more precise analysis of the procedures under the alternative proves that the stopping times, suitably normalized, have a standard normal limiting distribution. A few results from a small simulation study are also presented in order to give an idea of the finite sample behaviour of the suggested procedures.

A05 Use of a sequential method for monitoring safety in patients enrolled in the multicenter acute stroke trial

s 4 0 1 A05 USE OF A SEQUENTIAL METHOD FOR MONITORING SAFETY IN PATIENTS ENROLLED IN THE MULTICENTER ACUTE STROKE TRIAL F. Boutitie, J.P. Boissel, and M. Hommel Unit6 de Pharmacologic Clinique Lyon, France The Multicenter Acute Stroke Trial is a double-blind placebo-controlled randomized clinical trial aimed at evaluating the relative efficacy of a thrombolytic agent (streptokinase) in patients with a recent episode of acute ischemic stroke. The safety profile of the active treatment in this indication is not well known, but severe bleeding, including intracranial hemorrhage, can be expected. Hence, it was judged ethically essential to monitor patients' safety as closely as possible (with symptomatic cerebral hemorrhage as a primary criterion), while keeping the overall type I error rate at its predefined level. Sequential monitoring procedures are especially adapted for this purpose. The rationale for the choice of the Sequential Probability Ratio Test will be presented, as well as the design specifications. Also, results of power calculations obtained using simulated data will be shown, to demonstrate the effect of choosing expected rates of events which are not representative of the true rates in both study groups at the design stage. A06 CHANGING THE STUDY DESIGN DURING THE RECRUITMENT PHASE OF AN INTERNATIONAL PERINATAL MULTICENTRE CLINICAL TRIAL Jufie Weston, Mary Hannah and Arne Ohlsson Women's College Hospital Toronto, Canada Objective: To outline the process of changing the trial design during the recruitment phase of a mnlticontre clinical trial and to outline problems encountered. Material: The Term PROM Study was initially designed to compare induction of labour with expectant management in pregnant patients with prelabour rupture of membranes at term. Patients in the induction group received either intravenous oxytocin or vaginal prostaglandin to induce labour. Patients in the expectant group awaited spontaneous labour unless induction was indicated for medical reasons. Al~r recruitment into the trial had begun information became available suggesting that there may be differences in neonatal infection, caesarian section rates and maternal satisfaction between the two induction methods. Results: Following discussions with centre personnel, MRC and experts outside the trial, changes were felt to be necessary to create four study groups which would allow separate analysis of the two induction methods. These changes to the study design were made with a resulting increase in sample size to 5000 women. Conclusions: Many difficulties are encountered when the trial design is changed after recruitment has begun. However, after new information becomes available changes may be necessary in order to maintain the trial's clinical relevance. A07 DATA MANAGEMENT WORKLOAD ASSESSMENT FOR MEDICAL ONCOLOGY B. Troehanowski, C. Houston and C. Begg Memorial Sloan-Kettering Cancer Center New York, New York Investigators at our cancer center prepare many grant and contract proposals throughout the year. In order to improve our ability to project data management needs, we have developed a formula for assessing workload. This formula permits the estimation of the l?ercentage effort of a full time employee required to complete the data management activities. This ts of course a difficult task and we began by analyzing the work components of a medical oncology dsts manager's responsibilities. This includes a number of distinct phases as patients follow their treatment course. They are: accrual of new patients, active follow-up, and off-study follow-up. Each phase of a patient's treatment is assigned a multiplier based on how many hours per month the activity should require. However, these