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Record W2914452574 · doi:10.1177/1740774518824539

Challenges and solutions in the design and execution of the PROSPECT Phase II/III neoadjuvant rectal cancer trial (NCCTG N1048/Alliance)

2019· article· en· W2914452574 on OpenAlexaboutno aff
Deborah Schrag, Martin R. Weiser, Leonard B. Saltz, Harvey J. Mamon, Marc J. Gollub, Ethan Basch, Alan P. Venook, Qian Shi

Bibliographic record

VenueClinical Trials · 2019
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMedicineColorectal cancerFOLFOXOxaliplatinOncologyNeoadjuvant therapyClinical trialClinical endpointRandomized controlled trialInternal medicineSurgeryCancer

Abstract

fetched live from OpenAlex

BACKGROUND: More than half of the 40,000 incident rectal cancer patients in the United States each year are diagnosed at clinical stage II and III (locally advanced stage). For this group, high rates of cure can be achieved with the combination of pelvic radiation and sensitizing 5-fluorouracil (chemoradiation), surgery and chemotherapy, but treatment is long, arduous and toxicities are substantial. The PROSPECT trial (N1048, NCT01515787) was designed to determine whether neoadjuvant chemotherapy with 5-fluorouracil and oxaliplatin (FOLFOX) could be used as an alternative to neoadjuvant chemoradiation without compromising treatment outcomes and to spare these patients excess toxicity. The statistical design balanced the twin co-primary goals of achieving low local and distant recurrence rates. Study design features contended with the need for stringent safeguards given limited phase II data, the need for straightforward criteria to facilitate both accrual and protocol fidelity and the importance of patients' perspectives on symptom burden and treatment toxicity. METHODS: PROSPECT is an ongoing multi-site two-group seamless phase II/III randomized trial comparing standard neoadjuvant chemoradiation versus neoadjuvant chemotherapy with selective use of chemoradiation for patients with locally advanced rectal cancer. Challenges addressed in the design and conduct of PROSPECT have included the following: (1) setting safety thresholds given limited single-center phase II data, (2) establishing workable eligibility criteria, (3) balancing competing time to local and distant recurrence as co-primary endpoints and (4) obtaining reliable and complete data for patients' symptom burden. The design and implementation challenges, choices, modifications and their implications for the design of future national cooperative group clinical trials are presented. RESULTS: PROSPECT incorporated stringent thresholds for both complete surgical resection (R0) and the time to local recurrence as early stopping rules. When predetermined stopping criteria were not met after evaluation of the first 366 participants in the randomized phase II, the study transitioned seamlessly to phase III with cumulative accrual of over 1000 participants. Eligibility criteria stipulating rectal tumor location based on distance from the anal verge were unworkable, and the protocol was amended to a more pragmatic approach that assigned surgeons with primary responsibility for determining eligibility. Central radiology review was feasible and in some cases prompted discontinuation of protocol treatment. Participation in toxicity reporting using the National Cancer Institute's Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events was uniformly high and was well accepted by participants from over 200 sites in the United States, Canada and Switzerland. CONCLUSION: The strategies used to overcome these obstacles may inform the design of other studies that involve multi-modality treatment interventions, particularly trials where implementation of consistent criteria for eligibility and outcomes across hundreds of practice settings is necessary.

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 imitation

Not 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.

metaresearch head score (Codex)0.631
metaresearch head score (Gemma)0.496
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.631
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6310.496
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.003
Science and technology studies0.0030.008
Scholarly communication0.0070.006
Open science0.0060.005
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.479
GPT teacher head0.518
Teacher spread0.039 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations73
Published2019
Admission routes1
Has abstractyes

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