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 clinicaltrials.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 biostatisticians 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 advantage of adaptive design for breast cancer research are a reduction in overall time in the development of a drug, fewer patient required and 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.

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 clinicaltrials.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 biostatisticians 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 advantage of adaptive design for breast cancer research are a reduction in overall time in the development of a drug, fewer patient required and 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.

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 clinicaltrials.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 biostatisticians 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 advantage of adaptive design for breast cancer research are a reduction in overall time in the development of a drug, fewer patient required and 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.

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 clinicaltrials.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 biostatisticians 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 advantage of adaptive design for breast cancer research are a reduction in overall time in the development of a drug, fewer patient required and 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.