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Published on: February 12, 2022
A Clinical Primer for Defining Time Zero in Rectal Cancer Studies of Nonoperative Management: Implications for
Bailey K Hilty Chu1, Totadri Dhimal2, Megan Boyer2
1Surgical Health Outcomes Research Enterprise (SHORE), Department of Surgery, University of Rochester Medical Center, Rochester, NY, USA. Bailey_HiltyChu@urmc.rochester.edu.
Background:
Contemporary cancer research prioritizes clinical endpoints such as overall survival (OS) and disease-free survival (DFS). However, definition of the starting point, "time zero," for time-to-event analyses remains inconsistent in the rectal cancer nonoperative management (NOM) literature, affecting study comparisons. Moreover, the traditional definition of DFS for NOM is complicated given the success of salvage surgery for local regrowth (LR). Our aim was to evaluate how these definitions affect estimates of OS, LR, and DFS.
Methods:
We analyzed both a single-institution and a multi-institution cohort of patients with rectal cancer on NOM, shifting time zero from diagnosis to the post-treatment response assessment and to the date of clinical complete response (cCR) determination.
Results:
In the single-institution NOM cohort of 85 patients, shifting time zero from diagnosis to cCR determination led to a median 5-year OS decrease of 5% (87%→82%) and a 3-year LR rate increase of 4% (26%→30%). Importantly, the 5-year DFS increased by 23% (56%→79%) after excluding successful surgical disease salvage. In the multi-institutional dataset of 450 NOM patients, a shift of time zero from diagnosis to cCR determination led to a median 5-year OS decrease of 1.6% (94.2%→92.6%) and a 3-year LR rate increase of 1.1% (16.0%→17.1%). Five-year DFS increased by 8.3% (74.7%→83%) after excluding successfully salvaged disease.
Conclusions:
The range of definitions of time zero and DFS affect oncologic estimates in NOM for rectal cancer, particularly in datasets with smaller sample sizes, which may misrepresent oncologic outcomes. This underscores the need for standardization to ensure accurate comparisons across studies and guide shared decision-making.
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