ArticleJTCVS open2022
Time to treatment of esophageal cancer in Ontario: A population-level cross-sectional study.
Article in JTCVS open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Endoscopic resection versus esophagectomy for T1bN0M0 esophageal cancer: a systematic review and meta-analysis.Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus · 2026Pooled it
- A population-based study on the impact of social determinants of health on time to treatment of stage I lung cancer in Ontario, Canada.BMC cancer · 2026Article
- Association between surgery treatment delays and survival outcomes in patients with esophageal cancer in Hebei, China.Frontiers in oncology · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Timely cancer treatment improves survival and anxiety for some sites. Patients with esophageal cancer require specific workup before treatment, which can prolong the time from diagnosis to treatment (treatment interval [TI]). The geographical variation of this interval remains uninvestigated in patients with esophageal cancer. Methods: This retrospective population-level study conducted in Ontario used linked administrative health care databases. Patients treated for esophageal cancer between 2013 and 2018 were included. The TI was time from diagnosis to treatment. Patients were assigned a geographical Local Health Integration Network on the basis of postal code. Covariates included patient, disease, and diagnosing physician characteristics. Quantile regression modeled TI length at the 50th and 90th percentile and identified associated factors. Results: Of 7509 patients, 78% were male and most were aged between 60 and 69 years. The 50th and 90th percentile TI was 36 (interquartile range, 22-55) and 77 days, respectively. The difference between the Local Health Integration Network with the longest and shortest TI at the 50th and 90th percentile was 18 and 25 days, respectively. Older age ( Conclusions: Geographic variability of time to treatment exists across Ontario. Investigation of facility-level differences is warranted. Patient and disease factors are associated with longer wait times. These results might inform future health care policy and resource allocation.
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