We finally we over the 5 study design trials, TA, TE, TI, TV, TS. As we mentioned last time, TS acts like the outline of the puzzle, how can we fit the puzzles together? What are the relations between these five datasets?
Rather than focusing on individual datasets, today we will connect the 5 trial design datasets together with a good storyline!
FDA can use trial design, especially TS info to track and report the clinical study data for submission. Those Trial design datasets provide the standard info for reviewers to understand:
Recently my friend 77 told me they checked Trial Summary dataset for multiple rounds and fixed many miscellaneous issues. I wasn’t aware of the importance of the Trial Summary dataset until my colleague Jun told me FDA had a meeting emphasized on Trial Summary dataset on May.21.2021. So today we will go over the basics for the Trial Summary dataset. The Trial Summary domain presents a high-level view and key information from protocol about the trial in a structured format. It provides a complete study picture containing the trial phase, protocol title, trial objects, actual and planned arms…
Today we will go over Trial Inclusion/exclusion dataset. The TI datasets contain all the inclusion and exclusion criteria for the trial, such as subject age, lab or other findings, or maybe medical history. We can fetch the info from IE(inclusion/exclusion) dataset specifications or protocol.
Note: TI is NOT subject-oriented.
So today we will go over the essentials of the Trial Visit dataset, which includes the planned visit in a trial in the structure of One record per planned Visit per Arm. It will have effects on SV (study visit) domain.
ARMCD: if visits are NOT the same for all ARM, we will populate ARMCD.
*Might have duplicate records.VISITNUM: Visit Number is a numerical sequence according to protocol, eCRF or codebook.VISIT: Textual presentation of the numeric visit defined as per protocolVISITDY: Planned study day of visit is planned by the study protocol in numeric sequence.…
Last time we went over TA, Today we will go over Trial Element dataset. The trial Element domain contains all the info regarding the Elements included in the study, therefore the administration of planned trials uses Element as the basic building block to describe the time periods without any gaps.(Screening, Treatment, Followup). Each planned Element will have corresponding beginning and ending rules.
ETCD: Code value assigned to ELEMENT.
*TA dataset should be consist with TEELEMENT: indicates the assigned treatment
*TA dataset should be consist with TE, otherwise replace with "UNPLAN"TESTRL: identifies the event that marks…
Trial Design Datasets include TA (Trial Arms), TE (Trial Elements), TV (Trial Visits), TI (Trial Inclusion/Exclusion Criteria) , TS (Trial Summary) . These 5 Trial Design domains provided clear description of overall plan and design of the study. Today we will go over the basics for Trial Arms, it has the structure of one record per planned element per arm. It describes the sequence of Elements in each Epoch for each Arm.
STUDYID DOMAIN ARMCD ARM TEATORD ETCD ELEMENT
TABRANCH TATRANS EPOCH
ETCD: this code value assigned to the variable Element, it can be traced from the Trial…
Once, we need to check a define file, one of my colleagues found many miscellaneous issues, such as punctuation, typos in algorithms, and variable is not on the correct CRF pages. I was surprised by how meticulous he worked. Define file is the critical document while filing an FDA submission, so today we will go over the general structure of Define.pdf/ Define.xml for ADaM and SDTM.
One day, my friend 77 asked me which one is more important ADRG (Analysis Data Reviewer’s Guide) or define.xml? I think define.xml focuses more on the ADaM dataset level, whereas ADRG provides an overview storyline for the study or additional info besides Define.xml.
I decided to summarize the general format for the ADRG document.
Systemic Anti-Cancer therapy is collective to describe the treatment of cancer in conjunction with different categories of therapies such as: Surgical Therapies, Radiation Therapy, Stem Cell Transplants, Other Anti-Cancer Therapy. The ADPSATA: Prior systemic Anti-cancer Therapy dataset presented a key overview of patients’ prior systemic therapy treatments, which may lead to different efficacy endpoint for patients’ current treatments.
Regimen: Conventionally it identifies a standard or trial group of drugs given a specific way and may include other instructions concerning the timing and parameters of treatment. Subjects who received the same regimen multiple times will only be counted once.
One day, I need to validate SPM related files and ADSPM in a hematology study, I communicated with an experienced colleague many times and finally got the work done. Since each study has a different data structure, there is no standard SPM process available for all. I will share my experience with SPM work, hopefully, it is helpful in some way.
SPM (Second Primary Malignancy) is a good indication to access safety analysis in hematology studies. SPM, such as DNA damage, cytotoxic chemotherapy agents, may occur months/years after the original (primary malignancy ) was diagnosed and treated.