Alejandro A Schaffer, Ph.D.

The researchers have developed and distributed several software packages for pedigree analysis (FAST, CASPAR, PedHunter, IIC) and cancer genetics (oncotree, METREX). Users who need assistance with the software or who want to see new features added often send the researchers data files that include human data. The information is normally coded, and the researchers do not have access to the identification of the people whose information is in the files. Sometimes the content of the files gives rise to collaborations between the software developers and the providers of the files. Because concerns over the confidentiality of medical information have increased significantly over the past few years, the researchers must apply for exemptions from detailed ethics committee oversight for every data set they receive. This process is cumbersome and makes it difficult to assist software users. The amount of information required to apply for an exemption also poses a barrier to collaborations.

A full protocol will subject all data sets to ethics committee oversight without the need for individual exemption requests, enabling the researchers to assist users with software problems and to collaborate with other researchers.

From January 1, 2000, through December 15, 2001, the researchers received 71 requests for assistance, 19 of which included data files. None of the data files had any names or patient identifiers. Of these 19, in 8 cases the researchers sent back modified output files. In two of these eight cases, the researchers could see results of research interest; one of them concerned human data. In 2 of the 19 cases, the researchers sent back modified input files; in one such case, they established a collaboration with the originator of the files. In sum, most requests come under the heading of customer service, with no research contents. A few, however, do lead to research results or collaborations, for which ethics committee oversight is required.

Over the three-year time frame of this protocol, the researchers anticipate receiving data on a maximum of 10,000 individuals. They have modified their software documentation to explicitly instruct users to make sure the data files they send have no names. Should they receive files with names, they will delete the files and ask the originator to resubmit them with names encoded. Users submit data through unencrypted e-mail. The data are stored in password-protected computers at the National Institutes of Health.

We have developed software packages for pedigree analysis (FAST, CASPAR, PedHunter, IIC) and cancer genetics (oncotrees, METREX). The purpose of this protocol is to allow us to work on software problems reports that may contain human subjects data in them. The data should be coded, by which we mean that if there are any links between identifiers and names, we do not possess the links to decode the names. Occasionally our assistance leads to a more formal research collaboration. This protocol seeks to clarify the guidelines under which we can provide assistance to users of our human genetics software and to establish a formal procedure under which we can seek IRB approval for the serendipitous collaborations that arise from providing that assistance. We cannot predict the sizes of samples or the diseases studied in the data sets sent to us, so most of the medical aspects of this protocol are necessarily general. We rely on the data being coded and the collectors of the data having their own institutional approvals to protect against most risks. The scientific aspects of investigating problem reports cannot be hypothesis driven because we cannot guess what problems will arise. On the engineering side, the basic hypotheses are that: 1) our software is likely to contain some bugs or other weaknesses, which cannot be easily found except by having others use the software and 2) a good way to improve the functionality of the software is to encourage users to submit problem reports and other suggestions.

This protocol has been in effect since early 2002. The only amendments during that time were to set up three collaborations, as described in Sections 4.6 and 4.7 and 4.8. The protocol has been quite useful and no changes are proposed in procedures.

Exploratory Data Analysis for Disease Pedigrees and Cancer Genetics

National Human Genome Research Institute (NHGRI)

No intervention or sample collection is required on the study.

Lauren Lopez

Laura Macias

Nilesh Vora, MD

Angelei Pananganan

Jon Fukumoto, MD

Carrey Geoffroy

Pankaj Kumar, MD

Betsy Glowinski

Bert O'Neill

Leah Theisen

Tobias Meissner, PhD

Virginia Rhodes, MD

This study is a multisite, minimal risk, non-interventional study using patient electronic health record data collected as part of standard of care to answer cohort-based research questions and create robust real-world data sets.

One key purpose of the Study is to collect data that may be used for a wide range of scientific questions and real-world insights.

Umbrella Study for Analysis of Data Related to Patients With Cancer

Use data analysis to enable deeper understanding of patient population characteristics and outcomes to more accurately assess clinical trial feasibility and optimize trial design.

Use data analysis to generate supplemental data for new accelerated approval pathway filings and provide real world control arms where necessary.

Use data analysis to enable more precise characterization of biomarker testing rates, factors influencing access to testing, and uptake of recently approved therapies to inform commercial strategy for pharmaceutical companies and generate evidence for payors.

Use data analysis to support post approval understanding of longer term side effects that may not be sufficiently detected via randomized clinical trials.

Use data analysis to further understanding of variations in patient care across the US to help ensure patients have access to optimal testing and treatment.

Tempus AI

Aung Naing, MD

Primary Objective:

-Evaluate incidence of cardiac complications in Phase I patients.

Secondary Objective:

-To identify variables (i.e. number of electrocardiograms (EKG) performed) that lead to the detection of cardiac events.

The research plan includes a retrospective review of the chart of past UT MD Anderson Cancer Center (MDACC) patients and the experience in treating them.

All studies analyzed will be Phase I clinical trials.

Analysis is designed to collect information on the number of and timeframe within which ECGs are performed on these trials. Data on adverse events and serious adverse events, dose modifications based on ECG changes, attribution to drug, incidence and types of ECG changes specifically QTC prolongation as well as their influence on study procedures like dose limiting toxicities (DLTs) in dose escalation phase of the studies.

Study conducted using clinical records of patients treated on Phase I protocols in the MDACC Department of Investigational Cancer Therapeutics. The demographic data to be collected from patients whose charts will be analyzed will include variables such as age, gender, primary cancer, stage of the disease, performance status, treatment characteristics (i.e., number and type of prior therapies), disease status, adverse events, laboratory data (i.e., complete blood count/differential/platelets, tumor markers), and treatment outcomes.

The analysis will allow identification and descriptive analysis of the occurrence of cardiac events in the phase I population and will help define the role of protocol required EKGs in their detection.

HIPAA privacy and confidentiality guidelines will be followed. The database will be secured in the Department server. A Data coordinator has been recruited to undertake this project. The information derived from these observations will help the investigators formulate research questions and projects to develop future prospective studies.

The statistical analysis will be performed in a descriptive fashion with paired and multivariable analyses.

The analyses will be reported using summary tables, figures, and data listings. Continuous variables will be summarized using the mean, standard deviation, median, minimum, and maximum.

This study will be conducted at the MD Anderson Cancer Center in Houston, Texas.

The Role of the EKG in Anticancer Drug Development

The Role of the EKG in Anticancer Phase I Drug Development

Data review of studies, active between January 1, 2006 and December 31, 2009, who included ECGs in their safety evaluations. Use of identification and descriptive analysis of cardiac events occurrence in the phase I population to define role of protocol required EKGs in their detection. Statistical analysis performed in a descriptive fashion with paired and multivariable analyses.

M.D. Anderson Cancer Center

Research studies on new biomarkers conducted on previously banked blood and/or tumor tissue. Samples collected may include blood, fresh tumor tissue, urine, saliva, bone marrow, pleural fluid, ascites, skin or hair follicle.

Biomarker Research

Filip Janku, MD, PHD

The goal of this laboratory research study is to collect and analyze treatment, molecular profiling and biomarker data. The results of the data analysis will be used to better understand how to characterize tumors and identify therapies that may be tailored to individual patients and to identify and/or predict side effects that may occur and/or predict which therapies may be best for participants. Research may also be done on your existing tissue to identify new biomarkers.

Molecular Profiling/Deep Sequencing:

Molecular profiling is the classification of tissue based on the expression of certain genes within a tumor that might predict how the tumor responds to therapy. Deep sequencing is a more detailed type of molecular profile that allows for a more focused analysis of individual genes.

Biomarker Data:

A characteristic that is measured and evaluated as an indicator of normal biologic processes, disease processes or pharmacologic responses to a therapeutic intervention.

Study Participation:

If you agree to take part in this study, information from your medical record will be collected. The information that researchers will collect includes your medical history, chemotherapy schedule(s), as well as the results of any tests, procedures, and/or therapies you may have had. Your responses to the therapies, your side effects, and the results of any diagnostic tests performed during therapy will also be collected.

Researchers want to learn if they could have better predicted your response to therapy using the information collected in this study and/or better predict side effects from your treatment.

The data collected from your medical record will be stored in a password-protected database at MD Anderson to be used in research related to this study for up to 10 years.

In addition, research studies on new biomarkers may be conducted on your previously banked blood and/or tumor tissue. Samples collected may include blood, fresh tumor tissue, urine, saliva, bone marrow, pleural fluid, ascites, skin or hair follicle.

Your name, medical record number, and any other personal identifiable information collected from your medical record will be replaced with a code number. No identifying information will be directly linked to the data collected from your medical record. Only the doctor who is in charge of this study, and select members of their research staff, will have access to the code numbers and be able to link any of the data back to you.

Use of Samples:

Before your banked tissue samples can be used for research, the people doing the research must get specific approval from the Institutional Review Board (IRB) of MD Anderson. The IRB is a committee made up of doctors, researchers, and members of the community. The IRB is responsible for protecting the participants involved in research studies and making sure all research is done in a safe and ethical manner. All research done at MD Anderson, including research involving your tissue samples from this bank, must first be approved by the IRB.

Your tissue samples will be given a code number. No identifying information will be directly linked to your samples. Only the researcher in charge of the bank will have access to the code numbers and be able to link the samples to you. This is to allow medical data related to the samples to be updated as needed. Other researchers using your samples will not be able to link this data to you.

Length of Study:

Your participation in this study will be over after either the data, blood, tumor tissue samples, and/or archived tumor samples are analyzed.

This is an investigational study.

Up to 2000 participants will take part in this study. All will be enrolled at MD Anderson.

Samples collected may include blood, fresh tumor tissue, urine, saliva, bone marrow, pleural fluid, ascites, skin or hair follicle.

Profile Related Evidence to Determine Individualized Cancer Therapy (PREDICT) Program in Advanced Cancer Patients

For correlating marker profiles with response to treatment, univariate and multivariate (multiple covariates) logistic regression used, with response status taken as outcome variable. Distributions of time-to-event outcomes estimated using Kaplan-Meier curves, and these distributions compared among groups using log rank test.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Exploratory Data Analysis for Disease Pedigrees and Cancer Genetics	NCT00339508	Data Analysis Cancer Genetics		-	National Institutes of Health Clinical Center (CC)
Umbrella Study for Analysis of Data Related to Patients With Cancer	NCT06018753	Cancer		-	Tempus AI
The Role of the EKG in Anticancer Drug Development	NCT01462383	Advanced Cancer		-	M.D. Anderson Cancer Center
Exploratory Data Analysis for Disease Pedigrees and Cancer Genetics	NCT00339508	Data Analysis Cancer Genetics		-	National Institutes of Health Clinical Center (CC)
Profile Related Evidence to Determine Individualized Cancer Therapy (PREDICT) Program in Advanced Cancer Patients	NCT02160366	Advanced Cancer...	Biomarker Resea...	-	M.D. Anderson Cancer Center

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