Interim Analysis Task

An Interim Analysis Task is a Data Analysis Task that is conducted before the data collection task has been completed.

• Context:
  • It can range from being a Planned Interim Analysis Task to being a Unplanned Interim Analysis Task.
  • It (often) requires a clinical trial stopping criteria.
• Example(s):
  • data analysis conducted during Multicenter Automatic Defibrillator Implantation Trial (MADIT II);
  • data analysis conducted during phase 1 and phase 2 trials of an inactivated COVID-19 vaccine (Xia et al., 2020);
  • data analysis conducted during phases 1,2 and 3 of SARS-CoV-2 variant mRNA vaccine boosters (Choi et al, 2021;
  • data analysis conducted during the REASSURE Study (Dizdarevic et al., 2019);
  • …
• Counter-Example(s):
  • Clinical Efficacy Analysis Task,
  • Clinical Trial Participant Allocation Task.
• See: Clinical Trial, Clinical Dataset, Interim Clinical Trial Report, Clinical Research Data Management System.

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References

2022a

• (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Interim_analysis Retrieved:2022-3-20.
  • In clinical trials and other scientific studies, an interim analysis is an analysis of data that is conducted before data collection has been completed. Clinical trials are unusual in that enrollment of subjects is a continual process staggered in time. If a treatment can be proven to be clearly beneficial or harmful compared to the concurrent control, or to be obviously futile, based on a pre-defined analysis of an incomplete data set while the study is on-going, the investigators may stop the study early.

2022b

• (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Glossary_of_clinical_research#I Retrieved:2022-3-20.
  • Interim analysis
    • Any analysis intended to compare treatment arms with respect to efficacy or safety at any time prior to the formal completion of a trial. (ICH E9)

2021a

• (Choi et al., 2021) ⇒ Angela Choi, Matthew Koch, Kai Wu, Laurence Chu, LingZhi Ma, Anna Hill, Naveen Nunna, Wenmei Huang, Judy Oestreicher, Tonya Colpitts, Hamilton Bennett, Holly Legault, Yamuna Paila, Biliana Nestorova, Baoyu Ding, David Montefiori, Rolando Pajon, Jacqueline M. Miller, Brett Leav, Andrea Carfi, Roderick McPhee, and Darin K. Edwards (2021). "Safety and immunogenicity of SARS-CoV-2 variant mRNA vaccine boosters in healthy adults: an interim analysis". In: Nature Medicine, 27(11), 2025-2031.
  • QUOTE: The emergence of SARS-CoV-2 variants of concern (VOCs) and variants of interest (VOIs) with decreased susceptibility to neutralization has generated interest in assessments of booster doses and variant-specific vaccines. Clinical trial participants who received a two-dose primary series of the COVID-19 vaccine mRNA-1273 approximately 6 months earlier entered an open-label phase 2a study (NCT04405076) to evaluate the primary objectives of safety and immunogenicity of a single booster dose of mRNA-1273 or variant-modified mRNAs, including multivalent mRNA-1273.211. As the trial is currently ongoing, this exploratory interim analysis includes preliminary descriptive results only of four booster groups (n = 20 per group).

2021b

• (Meurer & Tolles, 2021) ⇒ William J. Meurer, and Juliana Tolles (2021). "Interim Analyses During Group Sequential Clinical Trials". In: JAMA, 326(15), 1524-1525.
  • QUOTE: Group sequential trials incorporate interim analyses to allow timely decisions that mitigate the challenges associated with uncertainty in the size and direction of the treatment effect. The data available at the time of the interim analysis are assessed to determine if predefined stopping criteria are met. This allows the trial to be stopped and a valid conclusion to be drawn earlier.

    When planning a group sequential trial, investigators must prespecify plans for interim analyses. This generally includes when the interim analyses will occur, what information will be used, and what statistical methods and stopping criteria will be applied. One action that may be triggered by an interim analysis is stopping enrollment due to clear evidence that the investigational treatment is superior (known as early success). During the interim analysis, a test statistic is calculated (eg, a P value), and, if the test statistic meets a prespecified threshold, the trial may stop. If the test statistic does not meet the threshold, the trial continues.

2020

• (Xia et al., 2020) ⇒ Shengli Xia, Kai Duan, Yuntao Zhang, Dongyang Zhao, Huajun Zhang, Zhiqiang Xie, Xinguo Li, Cheng Peng, Yanbo Zhang, Wei Zhang, Yunkai Yang, Wei Chen, Xiaoxiao Gao, Wangyang You, Xuewei Wang, Zejun Wang, Zhengli Shi, Yanxia Wang, Xuqin Yang, Lianghao Zhang, Lili Huang, Qian Wang, Jia Lu, Yongli Yang, Jing Guo, Wei Zhou, Xin Wan, Cong Wu, Wenhui Wang, Shihe Huang, Jianhui Du, Ziyan Meng, An Pan, Zhiming Yuan, Shuo Shen, Wanshen Guo, and Xiaoming Yang (2020). "Effect of an Inactivated Vaccine Against SARS-CoV-2 on Safety and Immunogenicity Outcomes. Interim Analysis of 2 Randomized Clinical Trials". In: Jama, 324(10), 951-960.
  • QUOTE: This was an interim analysis of 2 randomized placebo-controlled trials. In 96 healthy adults in a phase 1 trial of patients randomized to aluminum hydroxide (alum) only and low, medium, and high vaccine doses on days 0, 28, and 56, 7-day adverse reactions occurred in 12.5%, 20.8%, 16.7%, and 25.0%, respectively; geometric mean titers of neutralizing antibodies at day 14 after the third injection were 316, 206 and 297 in the low-, medium-, and high-dose groups, respectively. In 224 healthy adults randomized to the medium dose, 7-day adverse reactions occurred in 6.0% and 14.3% of the participants who received injections on days 0 and 14 vs alum only, and 19.0% and 17.9% who received injections on days 0 and 21 vs alum only, respectively; geometric mean titers of neutralizing antibodies in the vaccine groups at day 14 after the second injection were 121 vs 247, respectively.

2019

• (Dizdarevic et al., 2019) ⇒ Sabina Dizdarevic, Peter Meidahl Petersen, Markus Essler, Annibale Versari, Jean-Cyril Bourre, Christian la Fougere, Riccardo Valdagni, Giovanni Paganelli, Samer Ezziddin, Jan Kalinovsky, Inga Bayh, and Yong Du (2019). "Interim analysis of the REASSURE (Radium-223 alpha Emitter Agent in non-intervention Safety Study in mCRPC popUlation for long-teRm Evaluation) study: patient characteristics and safety according to prior use of chemotherapy in routine clinical practice". In: European journal of nuclear medicine and molecular imaging, 46(5), 1102-1110.

2016

• (Kumar & Chakraborty, 2016) ⇒ Amal Kumar, and Bhaswat S. Chakraborty (2016). "Interim analysis: A rational approach of decision making in clinical trial". In: Journal of advanced pharmaceutical technology & research, 7(4), 118.
  • QUOTE: Interim analysis is one of the reliable rational approaches to clinical trials that incorporate what is learned during the course of a clinical study and how it is completed, without compromising the validity or integrity. This method may encompass the potential changes in all program-related resources and activities, including changes in logistical, monitoring, and recruitment procedures.

    On a realistic level, the study not only requires the ability to measure the outcomes of interest continuously but also to make data and summarized information about those measurements available in a timely manner to different audiences according to the study role. In a clinical context, this means not just continuously tracking trial data collected on case report forms but also generating performance metrics that enable refinements in operations. Interest in this approach has mounted as a result of the soaring cost of clinical research and numerous trial failures, including, particularly, costly and well-publicized failures of major late-stage trials.

    The simplest result of such an interim analysis is early stopping for futility or continuation of the study. This rational approach also allows clinical researchers to employ the same basic management principles as typical modern businesses, using real-time data and analysis to inform decisions that continually optimize operations.

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