Adjusting the TMIST study design to accommodate slower than expected accrual: ECOG-ACRIN EA1151.
Bibliographic record
Abstract
TPS10614 Background: The ECOG-ACRIN Tomosynthesis Mammographic Imaging Screening Trial (TMIST), which opened in 2017, is a randomized trial designed to assess whether Tomosynthesis Mammography (TM) should replace Digital Mammography (DM) for breast cancer screening. It is hypothesized that women assigned to TM for 3-5 screening rounds will have fewer advanced breast cancers than the women assigned to DM. Advanced cancers are those that have distant metastases or positive nodes, are invasive tumors greater than or equal to 2.0 cm in size, or are invasive tumors greater than 1.0 cm in size that are triple negative or HER 2+. The initially planned enrollment of 164,946 women was due to be completed by the end of 2020, with follow-up concluded by 2025. There were substantial challenges in meeting this timeline, including the organizational and funding structure of the NCI National Clinical Trials Network which is dependent upon sites using their existing staffing resources (not always readily available at the time of study activation). This led to longer than anticipated start of enrollment for most interested sites and lower than anticipated annual enrollment per participating site based ultimately on the staffing support that could be allocated to manage TMIST. In addition, research staffing shortages and periodic research operations closures due to COVID-19 have also impacted enrolling TMIST sites, though unevenly, since the start of the pandemic. Enrollment plateaued at approximately 2,100 subjects per month by the end of 2020. With that accrual rate expected, the trial design was modified to reduce the sample size so that the study could be completed by 2027. Methods: With the approval of the NCI CIRB, we changed how the primary endpoint measure for TMIST is assessed from the number of advanced cancers that occur by 4.5 years after randomization to the time from randomization to occurrence of advanced cancers. All advanced cancers occurring within 7 years of randomization are now included and all participants followed for at least three years. In addition, the power of the study of the study was modified from 0.9 to 0.85, while the originally assumed effect size at 4.5 years was retained These changes allowed a reduction of sample size to 128,905, with subject recruitment projected to end in 2024. As of February 14, 2022, there are 125 sites open, 114 in the U.S. and 11 in other countries, with an additional 31 sites planning to open. As of February 14, 2022, a total of 63,845 women have been enrolled in the trial worldwide at 115 sites, with 20% of US participants self-identifying as belonging to minority racial and ethnic groups and 70% consenting to optional blood and/or buccal cell collection. Clinical trial information: NCT03233191.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.096 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".