Posts classified under: Data Studio

For this week only, we will meet in a basement classroom of the Center for Clinical Sciences Research: CCSR 0235 (Google Map). Please refer to the attached layout of Floor 0 and room photograph. The room should be accessible either via the elevators or stairway. If possible, please attend in person. I will try to enable the Zoom videoconference for those unable to attend in person.

TITLE: Clinical Implementation Study of Feasibility and Effectiveness of Pharmacogenomically-Guided Treatment in Gastrointestinal Cancer Patients

INVESTIGATORS:

Tinashe A. Mazhindu (1, 2, 3, 4)

Collen Masimirembwa (2, 4)

Ntokozo Ndlovu (3)

Margaret Borok (3)

(1) Chemical & Systems Biology Department, Stanford University School of Medicine

(2) African Institute of Biomedical Sciences & Technology (AiBST)

(3) Department of Oncology, University of Zimbabwe

(4) Consortium for Genomics & Therapeutics in Africa (CTGA) – iPROTECTA PROJECT

DATE: Wednesday, 5 April 2023

TIME: 1:30–3:00 PM

LOCATION: Room 0235, Center for Clinical Sciences Research (CCSR), 269 Campus Drive, Stanford, CA(http://maps.stanford.edu/ada/building-ada.cfm?FACIL_ID=07-590 )

WEBPAGE: https://dbds.stanford.edu/data-studio/

ABSTRACT

The Data Studio Workshop brings together a biomedical investigator with a group of experts for an in-depth session to solicit advice about statistical and study design issues that arise while planning or conducting a research project. This week, the investigator(s) will discuss the following project with the group.

INTRODUCTION

Pharmacogenomics (PGx) is the study of how genetic variations determine drug response and efficacy. The goal of PGx is to have molecular, genetic, and external phenotypic characteristics jointly guide prescribing the right drug, at the right dose, to the right patient, and have favourable outcomes with minimal toxicity. The clinical response rates to medicines for some cancers range from 25–80% which means a significant proportion of the cancer patient population may experience drug adverse drug reaction (ADR) with no clinical benefit whatsoever. These ADRs result in resource utilization in patient care through blood transfusion, use of colony-stimulating factors, hospitalizations, additional tests, and further treatment delays, a situation that is best kept to a minimum especially in resource-limited developing countries like Zimbabwe.

STUDY BASIS

Gastrointestinal (GIT) cancer accounts for approximately 20% of all new cancer cases in Zimbabwe and hence represents a significant disease burden. PGx recommendations are ranked according to strength of the evidence; 5-fluorouracil (5-FU), irinotecan, and analgesic have strong rankings. These drugs form the backbone of most first- and second-line therapies used in GIT cancers. In a newly published Pan-European study by Swen et al (2023), implementation of PGx guidelines by the Dutch Pharmacogenetics Working Group (DPWG) reduced the occurrence of adverse drug effects by 30%. Additionally, the study showed that the effect size of PGx guidelines differed among countries and different drug-gene pairs. However, only 1% of the participants in this study were Africans. Resource limitations call in to question the ability of African cancer treatment sites to implement PGx biomarker-guided therapy. Furthermore, such guidelines have limitations in an African setting because the populations possess distinct PGx biomarkers not found in Europeans.

 

STUDY DESIGN

This study is a single centre, PGx biomarker-guided implementation study to investigate feasibility and clinical effectiveness in gastrointestinal cancer patients. We will use reactive pharmacogenomic testing for DPYD, UGT1A1, CYP2D6, and CYP2C9 to guide therapy. Genotyping will be done using locally available next generation sequencing (NGS) capacity provided by the study sponsor. Patients will be enrolled into the study if they have an indication to receive chemotherapy inclusive of irinotecan and 5-FU (or its oral prodrug capecitabine) based on National Comprehensive Cancer Network (NCCN) guideline recommendations. Dosing will be based on the DPWG guidelines for their specific variants. Patients will be monitored through therapeutic drug measurements, NCI CTAE for toxicity, and disease response using RECIST criteria for up to 12 months with clinical reviews that include routine CT scans.

 

PROPOSED ENDPOINTS

Primary

• Dose deviation rate due to pharmacogenomics biomarker guidance and resultant drug/drug metabolite concentration at T_max
• Turnover time for pharmacogenomics results availability to clinicians to guide intervention decision making

Secondary

• Numbers and proportion of patients with ≥ grade 3 toxicity (NCI CTAE v5)
• Turnover time therapeutic drug monitoring results availability to clinicians to guide intervention decision
• Disease-free and overall survival of study participants at one year
• Tumour objective response rate (for neoadjuvant therapy or metastatic stage patients) using the RECIST criteria.
• Measure quality of life (QoL) scores among study participants using QoL questionnaires
• Number of samples bio-banked out of the total planned per patient.
• Cost-effectiveness of implementing PGx guided therapy

Exploratory

• PGx polymorphism impact of cancer supportive therapy outcomes- (analgesia and emesis)
• Cancer care biomarker and genomic mutation assessment for GI cancer patients including mapping the mutation trends

STATISTICAL ISSUES

The primary assistance I need is on statistical planning for the study.

1. What is the best study design for this implementation question and are these endpoints suited for such a study?
2. Retrospective data on adverse drug effects (ADR) before PGx usage is obtainable. Would this be a valid control for ADR and cost-effectiveness evaluation?
3. How do you calculate a sample size for such an implementation study?
4. How do you evaluate safety and dose deviation in such a study?

ZOOM MEETING INFORMATION

Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/91706399349?pwd=UXFlclNkakpmZC9WVWwrK244T2FwUT09

Password: 130209

Or iPhone one-tap (US Toll):

+18333021536,,91706399349# or

+16507249799,,91706399349#

Or Telephone:

Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or

+1 833 302 1536 (US, Canada, Caribbean Toll Free)

 

Meeting ID: 917 0639 9349

Password: 130209

International numbers available: https://stanford.zoom.us/u/abKRNREFBK

Meeting ID: 917 0639 9349

Password: 130209

SIP: 91706399349@zoomcrc.com

Password: 130209

TIME: 1:30–3:00 PM

LOCATION: Conference Room X-399, Medical School Office Building, 1265 Welch Road, Stanford, CA

ZOOM MEETING INFORMATION

Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/91706399349?pwd=UXFlclNkakpmZC9WVWwrK244T2FwUT09

Password: 130209

Note: No, this is not Data Studio Déjà Vu. Dr. Mazhindu needs advice about statistical planning for this complex implementation study. We will convene in the usual place: Conference Room X-399 of the Medical School Office Building. Zoom videoconferencing will be available for those unable to join us in person.

TITLE: Clinical Implementation Study of Feasibility and Effectiveness of Pharmacogenomically-Guided Treatment in Gastrointestinal Cancer Patients

INVESTIGATORS:

Tinashe A. Mazhindu (1, 2, 3, 4)

Collen Masimirembwa (2, 4)

Ntokozo Ndlovu (3)

Margaret Borok (3)

(1) Chemical & Systems Biology Department, Stanford University School of Medicine

(2) African Institute of Biomedical Sciences & Technology (AiBST)

(3) Department of Oncology, University of Zimbabwe

(4) Consortium for Genomics & Therapeutics in Africa (CTGA) – iPROTECTA PROJECT

WEBPAGE: https://dbds.stanford.edu/data-studio/

ABSTRACT

The Data Studio Workshop brings together a biomedical investigator with a group of experts for an in-depth session to solicit advice about statistical and study design issues that arise while planning or conducting a research project. This week, the investigator(s) will discuss the following project with the group.

INTRODUCTION:

Pharmacogenomics (PGx) is the study of how genetic variations determine drug response and efficacy. The goal of PGx is to have molecular, genetic, and external phenotypic characteristics jointly guide prescribing the right drug, at the right dose, to the right patient, and have favourable outcomes with minimal toxicity. The clinical response rates to medicines for some cancers range from 25–80% which means a significant proportion of the cancer patient population may experience drug adverse drug reaction (ADR) with no clinical benefit whatsoever. These ADRs result in resource utilization in patient care through blood transfusion, use of colony-stimulating factors, hospitalizations, additional tests, and further treatment delays, a situation that is best kept to a minimum especially in resource-limited developing countries like Zimbabwe.

STUDY BASIS:

Gastrointestinal (GIT) cancer accounts for approximately 20% of all new cancer cases in Zimbabwe and hence represents a significant disease burden. PGx recommendations are ranked according to strength of the evidence; 5-fluorouracil (5-FU), irinotecan, and analgesic have strong rankings. These drugs form the backbone of most first- and second-line therapies used in GIT cancers. In a newly published Pan-European study by Swen et al (2023), implementation of PGx guidelines by the Dutch Pharmacogenetics Working Group (DPWG) reduced the occurrence of adverse drug effects by 30%. Additionally, the study showed that the effect size of PGx guidelines differed among countries and different drug-gene pairs. However, only 1% of the participants in this study were Africans. Resource limitations call in to question the ability of African cancer treatment sites to implement PGx biomarker-guided therapy. Furthermore, such guidelines have limitations in an African setting because the populations possess distinct PGx biomarkers not found in Europeans.

STUDY DESIGN:

This study is a single centre, PGx biomarker-guided implementation study to investigate feasibility and clinical effectiveness in gastrointestinal cancer patients. We will use reactive pharmacogenomic testing for DPYD, UGT1A1, CYP2D6, and CYP2C9 to guide therapy. Genotyping will be done using locally available next generation sequencing (NGS) capacity provided by the study sponsor. Patients will be enrolled into the study if they have an indication to receive chemotherapy inclusive of irinotecan and 5-FU (or its oral prodrug capecitabine) based on National Comprehensive Cancer Network (NCCN) guideline recommendations. Dosing will be based on the DPWG guidelines for their specific variants. Patients will be monitored through therapeutic drug measurements, NCI CTAE for toxicity, and disease response using RECIST criteria for up to 12 months with clinical reviews that include routine CT scans.

PROPOSED ENDPOINTS

• Primary

Dose deviation rate due to pharmacogenomics biomarker guidance and resultant drug/drug metabolite concentration at T_max

Turnover time for pharmacogenomics results availability to clinicians to guide intervention decision making

• Secondary

Numbers and proportion of patients with ≥ grade 3 toxicity (NCI CTAE v5)

Turnover time therapeutic drug monitoring results availability to clinicians to guide intervention decision

Disease-free and overall survival of study participants at one year

Tumour objective response rate (for neoadjuvant therapy or metastatic stage patients) using the RECIST criteria.

Measure quality of life (QoL) scores among study participants using QoL questionnaires

Number of samples bio-banked out of the total planned per patient.

Cost-effectiveness of implementing PGx guided therapy

• Exploratory

PGx polymorphism impact of cancer supportive therapy outcomes- (analgesia and emesis)

Cancer care biomarker and genomic mutation assessment for GI cancer patients including mapping the mutation trends

STATISTICAL ISSUES

The primary assistance I need is on statistical planning for the study.

1. What is the best study design for this implementation question and are these endpoints suited for such a study?
2. Retrospective data on adverse drug effects (ADR) before PGx usage is obtainable. Would this be a valid control for ADR and cost-effectiveness evaluation?
3. How do you calculate a sample size for such an implementation study?
4. How do you evaluate safety and dose deviation in such a study?

ZOOM MEETING INFORMATION

Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/91706399349?pwd=UXFlclNkakpmZC9WVWwrK244T2FwUT09

Password: 130209

Or iPhone one-tap (US Toll):

+18333021536,,91706399349# or

+16507249799,,91706399349#

Or Telephone:

Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or

+1 833 302 1536 (US, Canada, Caribbean Toll Free)

Meeting ID: 917 0639 9349

Password: 130209

International numbers available: https://stanford.zoom.us/u/abKRNREFBK

Meeting ID: 917 0639 9349

Password: 130209

SIP: 91706399349@zoomcrc.com

Password: 130209