Thursday, October 30, 2014

Good Practice Designs: Biostatistics for Breast Cancer Trials

October is Breast Cancer Awareness Month, and CROS NT is addressing the implications of conducting clinical studies in breast cancer and how Sponsors can implement smart designs and strategies to conduct more efficient trials. 

Oncology is perhaps the most complex therapeutic area in clinical trials with over 450 indications and various unique characteristics like slow recruitment and long timelines to reach clinical endpoints. While breast cancer is just one indication, it is the most common cancer in women worldwide, and it is estimated that 1 in 8 women in the U.S. will be diagnosed with breast cancer during her lifetime. Early detection and screening along with treatment options such as medicines and hormone growth therapy have aided in making progress in curing breast cancer.

However, according to clinicltrials.gov, there are more than 2,000 ongoing breast cancer trials and approximately 1,000 ongoing in the EU according to its clinical trials register.

Good study designs in breast cancer trials can reduce the risk of failure in early phases. Oncology trials, particularly breast cancer trials, are unique for numerous reasons:
  • Use of various treatment combinations
  • Regimen modifications are likely during treatment
  • Slow recruitment
  • Numerous and complicated prognostic and predicative factors: age, menopausal status, hormone receptor status, etc.
  • Making the decision between adjuvant and neoadjuvant therapy
  • Determining HER2 status for possible monoclonal antibody treatment
What are the implications of these unique traits?
  • Study Design in early phases is extremely important: safety and efficacy, ethical considerations and long patient recruitment need to be taken into account
  • There will be vast amounts of data to analyze, including SAE safety data, and therefore biostatisticans will need access to real-time data in order to make go/no-go decisions.
  • Investing time in the proper design set-up of a breast cancer trial in the early phases is essential to increase success rates in later phases
Good Practice Designs: Involving the Biostatistician
The Statistical Analysis Plan for breast cancer trials, especially for Phase I trials, is extremely important in terms of determining trial design, sample size, endpoints and determining inclusion/exclusion criteria. The biostatistician should be involved in the beginning to consult on:
  • Protocol Development
  • Trial Design
  • Appropriate sample size calculation and possible recalculation
  • Defining Study Objectives and appropriate design
  • Defining the statistical method
  • Defining hypothesis and testing procedures
Good practice designs can speed up the planning phase enabling a reduction of time from the study synopsis to first patient in the study by defining adequate target criteria, interim analyses and specifying the most efficient statistical method for analysis. 

Considering an Adaptive Trial Design approach and consulting an expert biostatistician
Given the unique characteristics of breast cancer trials, Adaptive Trial Design can be an ideal statistical methodology for more efficient, cost-effective trials. It allows for the selection of the right target population for the drug. This is of special interest in the development of highly specific cancer drugs, which are only effective in a selected patient population, for example monoclonal antibodies. The advantages of adaptive design for breast cancer research are a reduction in overall time in the development of a drug, fewer patient required and the early availability of long-term safety data. Phase II/III seamless design has the possibility to select the right target population which is important for specific cancer drugs leading to fewer patients and quicker availability of safety data.

CROS NT & Breast Cancer
CROS NT has extensive expertise in conducting clinical studies in the oncology area - especially in the field of breast cancer. We have expert statisticians who have followed breast cancer studies from protocol design to reporting. CROS NT is also a supporter of breast cancer awareness and this month we raised funds for the National Breast Cancer Foundation at the Outsourcing in Clinical Trials OCT New England conference in Boston. 

Monday, September 29, 2014

RBM: Centralized Statistical Monitoring & Technology Considerations

On the 8th of October, CROS NT is sponsoring Nordic ePharma Day in Copenhagen. This event focuses on "Risk-Based Monitoring in Clinical Trials: a new approach for managing risk throughout the design, conduct and evaluation and reporting of clinical trials". 

Risk-based Monitoring (RBM) of clinical trials is an approach that combines on-site monitoring along with centralized remote monitoring by coordinating centers. Based on risk assessments about how the clinical information is captured and protocol designed, risk-based monitoring activities can be proactively supported by the usage of reporting tools. 

Leading up to this event, CROS NT discusses the considerations and impact of centralized statistical monitoring and which technology solutions will facilitate this approach. Centralized Statistical Monitoring (CSM) is the remote evaluation and analysis carried out by clinical trial personnel (e.g. clinical monitors, data managers, statisticians, etc) at a location other than on-site. This approach focuses on targeted data cleaning, subject level data review and statistical analysis to decide whether an on-site visit is triggered by risk. 

Why Centralized Statistical Monitoring (CSM)?

Centralized monitoring has been proposed as a new, more efficient approach to on-site visits. A CSM approach can be useful in detecting faulty equipment errors, negligence or fraud, protocol deviations and unexpected patterns which then identifies the sites that need further investigation.

Centralized monitoring techniques can be applied to:
  • The monitoring of data quality through routine review of submitted data to identify different types of errors
  • The identification of data trends not easily detected on-site like data consistency and accuracy or missing data
  • The analysis of site characteristics which aids in defining poorly performing sites
  • The verification of critical source data remotely
  • The completion of administrative/regulatory tasks
CSM has been suggested as a cheaper and more efficient alternative to on-site monitoring. Source Data Validation is usually time consuming and not as effective at identifying potential risks. A CSM approach performs data quality checks on all trial centers at the subject and site level. Statisticians can then analyze the data in real time to identify sites that need further investigation due to unusual data patterns.

The main errors found at the participant level are incorrect dates and outlying values. Meanwhile, at the site level, data discrepancies can be found when rounding numbers, comparing mean/average results, analysis of variability, inliers and correlation checks. In a CSM strategy, many of these discrepancies can be improved using technology solutions.

Technology Considerations

Electronic Data Capture is an essential part of an RBM technology strategy since it captures data in real time. EDC allows Investigators to capture and monitor site activity and captures data and determines which data need to be verified and analyzed. Although most EDC systems provide built-in reports to support data management activities, other metrics and information which are needed to verify the risk-based approach are not provided to final users.

Therefore, analytical business intelligence tools should be considered. By using a business intelligence tools to query the EDC database, reports can be designed depending on the target audience involved in the trial review including project and data managers, site staff, clinical monitors and safety staff. Reports with centralized monitoring metrics that assess site activity can be easily made available for quick analysis and decision-making.

Clinical data visualization and analysis are especially important to aggregate data across multiple systems and even multiple studies. An added value is the ability to drill-down data and click-through multiple levels of detail. Tools available today are generally cloud-based which means Sponsors avoid the technology hassle of HTML or plug-ins and enjoy the convenience of data "on the go". 

Nordic ePharma Day

Join CROS NT in Copenhagen on the 9th of October for Nordic ePharma Day to be part of the discussion on RBM in clinical trials. For more information visit the event website.



Monday, September 22, 2014

Making the Connection between Centralized Biometrics & Adaptive Trial Design

Flexible study designs are gaining popularity in clinical research as sponsors search for ways to reduce study timelines and costs by making modifications along the way. Implementing Adaptive Trial Design has been one flexible design that has proven successful for many clinical trials with 20-30% of trials now using this methodology. However the degree of success of this design approach doesn't just depend on the capabilities of your biostatistician. It can also depend on your outsourcing model.

CROS NT looks at the connection between a centralized biometrics outsourcing approach and adaptive trial design success.

In an adaptive approach, at each stage of the study and and in each phase of the drug or device development cycle, the probability of success is quantified and the study team is fully informed in order to evaluate risks and benefits associated with each decision. This begins with the protocol where scenario planning acts as a critical "stress test" key tool for demonstrating the value of adaptive design.

Ways of maximizing efficiency through adaptive designs are:
  • Early stopping (futility, early rejection)
  • Change in treatment allocation ratios
  • Alterations of hypothesis (non-inferiority vs. superiority)
  • Use of different test statistics
  • Sample size re-assessment
  • Dropping/adding treatment arms
  • Select special populations (inclusion/exclusion criteria)
  • Combination of trial phases (adaptive seamless design)
These are generally statistical concerns, therefore where does the centralized biometrics outsourcing model fit in?

It is generally agreed that the best time to involve a biostatistician in a clinical study is at the very beginning. This allows the biostatistician to understand the study design and make suggestions on hypothesis testing and analysis and also ensures continuity throughout the study team. If one study team - including the biostatistician - is assigned to trial design, data analysis and medical communications from the start, common data standards can be applied throughout the drug development process. This is a centralized approach to data collection and analysis.

As planning is an important step in preparing and implementing an adaptive design approach, there should be a good communication plan defined between the CRO and Sponsor. Agreeing on a statistical analysis plan, methodologies and programming formats can reduce the number of reviews, therefore saving time and costs.

In order for statisticians to make "go/no-go" decisions, they need access to real time data as soon it is collected. This can be achieved through a centralized approach when all data are stored in a central data warehouse and/or archive which avoids having to keep track of multiple repositories. 

The biostatistician really does collaborate with the rest of the study team, including Data Managers, Statistical Programmers and Medical Writers. Regarding Data Management, the biostatistician can assist with CRF development and dataset specifications. Working with statistical programmers, methodological statisticians ensure data formatting is correct and select data to be pooled. These interactions all contribute to the biostatistician's statistical analysis that lead to adaptations in a trial such as the decision to recalculate the sample size, alter study endpoints or even terminate a study. When the study data is dispersed among various sources, it becomes more time consuming for the biostatistician to gather the data needed and calls in question the quality of the data being pooled.

Some studies have already suggested that the implications of adaptive designs could save Sponsors between $100-200 million USD per year. Those savings, coupled with the considerable 30-40% cost savings of a centralized biometrics approach, due mostly to global libraries and achieved efficiencies through one project team, can result in significant cost savings for trial Sponsors.

CROS Academy: "Introduction to Adaptive Trial Design" Course

We are offering three courses this fall in adaptive trial design. These courses are designed to teach clinical trial professionals about the adaptations possible in a trial and how to use the proper statistical methodology.

"Introduction to Adaptive Trial Design" is being offered:


Tuesday, September 9, 2014

How well do you understand the role of Biostatistics in Clinical Research?

Statistics plays a crucial role in clinical trials and the drug development process - from trial design to protocol development. Having a fundamental understanding of statistical issues can uphold the integrity of a clinical trial and improve communications between clinicians and statisticians. 

As a clinical trial professional, non-statistician, are you familiar with the following statistical concepts?
  • Confidence intervals
  • Multiplicity
  • Subgroup Analysis
  • Parametric vs. Non-parametric statistical methods
  • Sample Size Calculation
  • Types of endpoints
  • Statistical Reporting
  • Missing Data
  • Adaptive Trial Design
  • Bayesian Model
Biostatistics are involved in every step of clinical research including trial design, protocol development, data management and monitoring, data analysis and clinical trial reporting. A Harvard report on clinical research demonstrated evidence that suggests the researchers often misinterpret statistical methods due to poor knowledge of statistical concepts.

Statisticians and clinical operations personnel must always communicate in order to ensure successful trial design and analyses. A factor that can often hinder effective communication is complicated statistical terminology. Since statisticians can specialize in study designs, even complex designs like Adaptive Trial Design, therapeutic areas and statistical methods, it is crucial that the rest of the study team understands the statistical strategy proposed by the biostatistician.

Why is it so important to understand the role of the biostatistician?
How well do you understand the statistical elements in these areas of clinical research?
  • Protocol Development & Design
  • Data Management
  • Study Implementation
  • Study Monitoring
  • Data Analysis & Reporting
The biostatistician works closely with the rest of the biometrics team and management throughout the study including Data Managers, Statistical Programmers and Medical Writers. Regarding Data Management, the biostatistician can assist with CRF development and dataset specifications. Working with statistical programmers, methodological biostatisticans ensure data formatting is correct and select data to be pooled. In terms of medical writing, biostatisticians will often write the statistical part of the Clinical Study Report.

In the Statistical Analysis Plan (SAP), the biostatistician will outline study endpoints, sample size calculation, interim analysis planning and the hypothesis and testing procedures. Perhaps the most well-known responsibility of the biostatistician is the definition of sample size which involves several factors that influence the size of the study, timelines and budget requirements. 

Therefore, how well do you really understand these concepts when it comes to evaluating clinical research results?

CROS Academy's Course: "Understanding the Statistical Elements of a Study Protocol - for Non-Statisticians"
CROS Academy is hosting two courses on introducing the statistical elements of a study protocol to non-statisticians. This course is offered to clinical trial professionals who wish to comprehend the role of statistics and statisticians in clinical research. The course aims to enhance one's understanding of basic statistical principles as well as the statistician's view on clinical trial aspects.

Course dates:
26 November 2014 in Paris, France - Download the brochure
01 December 2014 in London, UK - Download the brochure

Friday, August 29, 2014

Interview ICT: CROS NT Discusses European Clinical Data Transparency Legislation

CROS NT's Global Head of Business Development & Marketing, Chris Hamilton, was recently interviewed by International Clinical Trials magazine regarding the European legislation on clinical data transparency, its implications and how to prepare. 

ICT: New European legislation in 2016 will require summaries of trials to be made public - what will change?

Chris Hamilton (CH): There is already a register of all clinical trials, but new draft European law mandates the publication, via a publicly accessible database set up by the EMA, of summaries of trials that have reached marketing authorisation. That will give very useful information to anyone interested in a particular therapeutic area and indication.

ICT: How is the new system being received by the industry?

CH: Many large pharma companies are already making such summaries available to the public, indicating good acceptance of the initiative. What is more contentious is the promotion of making raw data available, not just the summaries. Some companies have decided to challenge the draft mandate, so it will be interesting to see what happens.

ICT: What do you think the main benefits of greater data transparency will be?

CH: The sharing of information on completed research will be a positive contributor to the overall development of medicinal products by avoiding repetition of similar studies and generating ideas for product extensions for use in other indications. Initiatives such as the publication or risk management plans will also enhance patient safety.

ICT: What about patient confidentiality and privacy - how can this be protected?

CH: All stakeholders seem committed to ensuring patient confidentiality is protected. This is one of the key topics in debating the requirement to make data, not just summaries, available to the public. I expect that sponsors will need to introduce clear guidelines on how to ensure any possible patient identifiers are removed from trial data prior to publication, while maintaining the traceability of trial results.

ICT: How will the legislation impact sponsors and how should they prepare?

CH: The ultimate aim is to make it mandatory for sponsors to respond to reasonable requests from the public to access the data, not just the final results, collected during clinical trials. Sponsors can prepare by establishing how and when data can be anonymised, and in what format the data needs to be held so it is easily accessible. Identifying resources to prepare the data for the EU portal will also be important.

ICT: You advocate a more centralised approach to data - why?

CH: There are significant efficiencies to be gained by centralising data for a particular product. For example, the re-use of material from one study to the next saves around 30-40% of time and cost for database setup and statistical programming. Utilising the same data collection technologies and maintaining knowledge through team continuity makes studies run more smoothly.

Centralising data also allows you to apply standard formats. Taking this approach continues to facilitate the use of various clinical CROs, but it makes more sense to keep the data with one team.

Companies that plan for a pre-market sale of their compound and intellectual property can be assured of a certain valuea dd if they can show that all the data, analysis and reports on the drug development thus far can be located centrally in a consistent format. 

ICH: Tell us about clinical data visualisation tools and how they fit in.

CH: Clinical data visualisation tools can be an important component for sponsors conducting trials that need to make more informed decisions and make sense of clinical data which could eventually be shared publicly. They can be particularly useful for researchers looking at completed study data.

These tools facilitate drill-down and click-through to multiple levels of detail, allowing for the analysis of specific subsets and subpopulations. They allow researchers to make crucial decisions based on the information and trends revealed. 

As a CRO specialized in biometrics, CROS NT helps companies with their regulatory submissions to the EU and USA by preparing their clinical data in a reliable and traceable way. If you'd like more information on centralized biometrics, clinical data transparency or would like to consult one of our experts, please visit our website.

Wednesday, August 20, 2014

Implementing Smart Clinical Data Strategies for Timely Post-Market Studies

Regulatory authorities such as the FDA and EMA are increasingly stressing the importance of timely post-market studies in order to determine the safety and efficacy of drugs already on the market in order to update drug labelling if necessary.

In the medical device sector, regulatory authorities are putting pressure on companies to prove the safety of a device in use and are requiring more post-market study data. In particularly in the EU, in an effort to guarantee patient safety, more PMCF (Post-Market Clinical Follow-up) studies and safety surveillance has been proposed including harmonization among EU member states in terms of market surveillance.

Therefore, how can companies conduct their post-market studies in a cost-effective manner while meeting the "timely" demands of regulatory authorities?

CROS NT suggests effective techniques for managing your post-market study data that will guarantee cost control, efficiency and regulatory compliance:

1. Implementing data management strategies for the management of vast amounts of data from large patient populations.
The use of a Global Library can significantly reduce DM costs by re-using forms - cost reductions of up to 50% if implementing the centralized biometrics outsourcing model. This guarantees a uniform traceability of data, better preparation of data traceability, due diligence ready datasets and documentation and one single Project Manager.

2. Implementing and/or Mapping to CDISC standards for regulatory acceptance.
It is important to start implementing CDISC standards during data collection by having Data Managers design the CRF using CDASH standards. This makes the the process of mapping data into SDTM and ADaM datasets much more straightforward. Identifying the right process for implementation and choosing the appropriate technology can reduce the costs of adopting these standards.

3. Implementing technology solutions such as eClinical platforms with EDC/ePRO/IWRS/CTMS in order to collect and analyze data in real time
Biostatisticians need to be able to make crucial and informed decisions. An eClinical, cloud-based solution allows for real-time study management, access to data from any device and flexibility of contracted resources. Using the same ePRO/EDC/IWRS reduces set-up, training and HelpDesk costs and allows for easy data integration.

With cloud-based eClinical applications, key performance indicators and the creation of clear Service Level Agreements with CROs becomes more achievable.

4. Implementing clinical data visualization tools that allow Sponsors to make sense of clinical data immediately.
The return on investment from the implementation of data visualization tools is the amount of time saved by being able to access and analyze data immediately and using that data to identify and fix problems.

Business Intelligence tools are the best technology option for Data Visualization, especially if implementing a Risk-Based Monitoring approach. They allow for data retrieval, report development from different data sources, report delivery and cloud-based technology. Web-based applications can be accessed from various devices including PC/laptops, smartphones and tablets.

Have an upcoming post-market study in the drug or device development cycle? Contact CROS NT for clinical data and technology solutions that fit your study and budget needs.


Monday, August 11, 2014

Statistical and Technology Solutions for Streamlining Orthopedic Device Trials

According to a recent report (Millennium Research Group), the orthopedic device market is growing steadily, and this is due to several changing factors in the industry. There has been a significant increase in devices for the treatment of extremities including devices for hands, wrists, elbows, shoulders, feet and ankles. This market change is due to both an aging population that is still physically active and an increase in the number of sports related injuries. 

What does this mean for device development and clinical trials?
Orthopedic device development is a rather saturated market, however device companies have the opportunity to develop new devices to meet market demand and streamline trial costs for more "mature" products such as hip implants through a clinical trial strategy that combines smart trial design and integrated technology. 

Combining the right statistical solutions with an eClinical platform can result in up to 20-30% cost savings.

Statistical Solutions
Reducing uncertainty in the planning phases of orthopedic device development can eventually reduce timelines, and inevitably costs. Statistical methods in device studies test for proof of safety and efficacy and also an estimation of effects.

Involving an expert biostatistician from the beginning can help with the protocol development and study design, especially in the areas of adaptive trial design. Since statisticians in orthopedic device trials must balance potentially expensive products, long follow-up periods, possibly large sample sizes, and unique endpoints, adaptive trial design can help account for these changes. The FDA accepts the use of Bayesian design in medical device trials since it combines data from previous studies and the ongoing study to make changes to the study if necessary which can reduce timelines.

Clinical trial managers should also consider the following:
  • Smart Trial Design & Methodology including solutions for adaptive trial designs: adaptive design in orthopedic trials allow statisticians to make mid-course corrections, include fewer patients if possible and reduce timelines.
  • Consultancy from statisticians experienced in medical device trials for power/sample size calculations and specific analyses for orthopedic implant studies: composite endpoints, pain assessments, radiographic data and QoL measures
  • CDISC compliant datasets: consider that the FDA will soon require CDISC-compliant datasets; meaning the statisticians need to be expert in these standards
Integrated, Cloud-Based Technology
To reduce costs in orthopedic device development, an integrated eClinical platform can provide immediate feedback, more accessible trial information and higher data quality. It can facilitate an adaptive approach, or in the case of a trial that is showing a negative trend, it can allow early termination, thereby reducing the risk to patients and reducing the cost of the trial.

An integrated platform that bundles EDC/ePRO/IWRS/CTMS in the cloud provides the following benefits:
  • Sponsors can negotiate enforceable expectations for clinical data entry into the eClinical application
  • Move away from time based unit of measurements to activity-based measurements
  • Standard ad hoc reports
  • Industry and regulatory compliant archival records
CROS NT has expertise in conducting medical device trials in both the US and Europe and has represented many companies on regulatory panels. We have particular expertise in orthopedic and implant studies and have completed more than 60 studies in just the past 5 years including successful submissions in the treatment of knee pain, heel pain, THR, hip resurfacing, cartilage replacement, fusion products, artificial discs and bone growth simulators. We have also been involved in several non-inferiority trials for the lumbar and cervical spine. We have expert biostatisticians with over 25 years of experience in the medical device field with a track record of FDA panel representation for medical device submissions and proven expertise in adaptive trial design.

CROS NT joined the DATATRAK Partner Connect Program in 2013 to provide an eClinical platform with EDC/ePRO/IWRS/CTMS to reduce study costs and improve the device development process.