Case Study on Randomization in Metastatic Breast Cancer
Geography: N/A
Type Service: N/A
Background/Client Requirement:
A leading global pharma healthcare provider, driven by a commitment to delivering care and nurturance for the patients through innovation and science, has collaborated with Techsol Lifesciences to conduct biostatistical activities for the clinical evaluation of their new oncology therapeutic drug. This Phase III study, focused on previously untreated patients with Human Epidermal Growth Factor Receptor 2 (HER2) positive metastatic breast cancer (MBC), ensuring compliance with Regulatory Authorities.
Project Objectives:
The purpose of this study is to compare the efficacy, safety, pharmacokinetic, and immunogenicity of drug (Test) plus Trastuzumab and Docetaxel versus drug (Reference) plus Trastuzumab and Docetaxel treatment in previously untreated patients with HER2 positive MBC.
Challenges:
- Ensuring that the sponsor fully understands the randomization method selected, including the allocation ratio, block size, and the total number of subjects or vials generated, as defined by the CRO statistician.
- Patient characteristics may vary by site, and enrollment rates may differ, making it essential to maintain treatment balance across centers. Without careful planning, these differences can result in imbalances, that could confound the assessment treatment effect.
- The risk of dropout is significant due to the prolonged follow-up and severity of disease. Dropouts can lead to a loss of statistical power and affect the balance of treatment groups.
- An adequate number of treatment vials or allocations must be generated in advance to meet the demand across sites. Insufficient vials can disrupt the study flow, while excess vials can lead to waste.
- Block size needs to be carefully chosen to maintain blinding and ensure treatment balance. Inadequate block size can increase the risk of treatment assignment predictability, especially if enrollment rates are low at certain sites.
Techsol Solution/Approach:
- Our in-house statisticians develop a comprehensive and accessible randomization plan that clarifies all technical aspects for the sponsor. This plan includes a detailed description of the chosen randomization method, outlining the allocation ratio, block size, and their importance in ensuring balanced treatment groups. Additionally, it should outline the total number of subjects or vials generated, providing rationale for these choices. Regular updates throughout the trial on randomization progress and any relevant data changes can reinforce transparency. This approach ensures that the sponsor remains informed and engaged, facilitating alignment and regulatory compliance.
- Implement a stratified block randomization process by site, ensuring balance in treatment assignments within each center. Using SAS macros, create blocks specific to each site or center, controlling the allocation ratio to maintain balance.
- Plan for dropouts by generating extra randomization slots or treatment allocations. Additionally, implement an adaptive design that allows for re-randomization if necessary, or employ imputation methods to handle missing data without compromising treatment balance.
- Estimate the required number of vials based on site enrolment rates and anticipated dropouts. To avoid overproduction, used a centralized inventory management system to monitor the distribution and usage of vials across sites in real-time.
- Determined block sizes based on anticipated enrolment patterns, ensuring they are small enough to maintain balance within sites but large enough to protect blinding. Randomizing the block size (e.g., using variable block sizes) can also help reduce the predictability of treatment allocation.
Project Achievements:
- Creating a clear and detailed randomization plan lead to better understanding by the sponsor and ensured alignment on the key randomization details. This approach promoted transparent communication, minimized misunderstandings, and ensures adherence to the protocol. It also facilitates regulatory review by providing a well-documented and accessible account of the randomization process, thereby supporting the overall credibility and reliability of the study’s design.
- Ensuring balanced treatment groups across all centers, minimized site-specific bias, enhancing the internal validity of the study.
- The study maintained sufficient statistical power, minimizing potential bias and ensuring that the trial remains robust and adequately powered despite participation attrition.
- Optimizing the number of vials enhances operational efficiency and minimizes delays, supporting seamless trial conduct, and reducing resource wastage.
- Selecting an appropriate block size maintains the integrity of randomization, minimizes selection bias, and helps uphold blinding, thereby improving the study’s internal validity.
- This approach ensured unbiased statistical analysis, by having the blinded statistician work with de-identified data and preserving the integrity of the randomization process. The study’s results remain credible and reliable, free from any bias due to inadvertent unblinding, while the randomization process is transparent and compliant with regulatory requirements.
The Outcome:
- The implementation of a well-designed randomization plan in this multi-center oncology trial successfully ensured methodological rigor, operational efficiency, and robust data integrity. By employing site-specific stratified randomization, the study achieved balanced treatment allocation across multiple centers, minimizing potential confounding from site-specific characteristics. Thoughtful planning for dropout rates ensured the trial maintained statistical power despite patient attrition, while generating an optimal number of treatment vials supported seamless operations without resource wastage.
- The use of randomized block sizes maintained blinding integrity, reducing predictability and selection bias in treatment allocation. Furthermore, adherence to strict blinding protocols and a secure, well-documented unblinding process helped protect the study’s validity, preventing inadvertent unblinding and ensuring objectivity in outcome assessment.
- Collectively, these strategies led to high-quality data and enhanced trial credibility, supporting reliable conclusions about the treatment’s efficacy and safety. This structured approach not only safeguarded trial integrity but also facilitated smooth regulatory review and streamlined operational workflows, delivering a successful, scientifically robust project outcome.