Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Whole-genome sequencing reveals genomic characterization of <i>Listeria monocytogenes</i> from food in China.

Frontiers in microbiology·2023
Same author

A novel TBK1/IKKϵ is involved in immune response and interacts with MyD88 and MAVS in the scallop <i>Chlamys farreri</i>.

Frontiers in immunology·2023
Same author

Zeolite-seed-directed Ru nanoparticles highly resistant against sintering for efficient nitrogen activation to ammonia.

Science bulletin·2023
Same author

Clinical outcomes of vinorelbine loading CalliSpheres beads in the treatment of previously treated advanced lung cancer with progressive refractory obstructive atelectasis.

Frontiers in bioengineering and biotechnology·2023
Same author

Coaching Leadership and Employees' Deviant Innovation Behavior: Mediation and Chain Mediation of Interactional Justice and Organizational Identification.

Psychology research and behavior management·2023
Same author

Relationship between vitamin D status and cardiac autonomic neuropathy in prediabetes.

Asia Pacific journal of clinical nutrition·2022
Same journal

A Mixture of Distributed Lag Non-Linear Models to Account for Spatially Heterogeneous Exposure-Lag-Response Associations.

Statistics in medicine·2026
Same journal

Practical Considerations for Gaussian Process Modeling for Causal Inference in Quasi-Experimental Studies With Panel Data.

Statistics in medicine·2026
Same journal

Covariate Adjustment for Wilcoxon Two Sample Statistic and Test.

Statistics in medicine·2026
Same journal

Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions.

Statistics in medicine·2026
Same journal

A Causal Framework for Evaluating the Total Effect of Strategies Aiming to Expand Screening and to Improve Outcomes.

Statistics in medicine·2026
Same journal

Causal Effects on Nonterminal Event Time With Application to Antibiotic Usage and Future Resistance.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: Jun 18, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

A conditional maximized sequential probability ratio test for pharmacovigilance.

Lingling Li1, Martin Kulldorff

  • 1Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Ave., 6th floor, Boston, MA 02215, USA. lingling_li@post.harvard.edu

Statistics in Medicine
|November 27, 2009
PubMed
Summary
This summary is machine-generated.

A new conditional maximized sequential probability ratio test (CMaxSPRT) improves drug and vaccine safety surveillance. This method accounts for uncertainty in expected event counts, reducing bias in rare adverse event detection.

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Related Experiment Videos

Last Updated: Jun 18, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Area of Science:

  • Pharmacovigilance and Drug Safety
  • Biostatistics
  • Epidemiology

Background:

  • Post-marketing surveillance is crucial for detecting rare adverse events missed in clinical trials.
  • Sequential probability ratio tests (SPRTs) are used for timely detection of safety signals.
  • Existing SPRTs can be biased when historical data for estimating expected event counts is limited.

Purpose of the Study:

  • To introduce a novel statistical test, the conditional maximized sequential probability ratio test (CMaxSPRT).
  • To address the bias in SPRTs caused by uncertainty in estimated expected event counts.
  • To improve the accuracy and reliability of drug and vaccine safety surveillance.

Main Methods:

  • Development of the conditional maximized sequential probability ratio test (CMaxSPRT).
  • Incorporation of randomness and variability from both historical and surveillance data.
  • Evaluation of CMaxSPRT's statistical power under various scenarios.

Main Results:

  • The CMaxSPRT adjusts for uncertainty in expected event counts, mitigating bias.
  • The new test integrates variability from historical and real-time surveillance data.
  • Statistical power evaluations demonstrate the effectiveness of CMaxSPRT.

Conclusions:

  • CMaxSPRT offers a more robust approach to pharmacovigilance compared to traditional SPRTs.
  • This method enhances the ability to detect rare adverse events early and reliably.
  • CMaxSPRT is a valuable tool for improving public health through safer drug and vaccine monitoring.