Evidence map›Paper›PMID 35132892›Full record

ArticleAnnals of the Royal College of Surgeons of England2022

Evaluating potential delays and outcomes of patients undergoing surgical resection for locally advanced and recurrent colorectal cancer during a pandemic.

M A Javed, A Kohler, J Tiernan, A Quyn, P Sagar

Abstract read
In one paragraph

Article in Annals of the Royal College of Surgeons of England, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Observational
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

M A JavedThe Leeds Teaching Hospitals NHS Trust, UK.
A KohlerThe Leeds Teaching Hospitals NHS Trust, UK.
J TiernanThe Leeds Teaching Hospitals NHS Trust, UK.
A QuynThe Leeds Teaching Hospitals NHS Trust, UK.
P SagarThe Leeds Teaching Hospitals NHS Trust, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe COVID-19 pandemic resulted in a significant disruption of colorectal cancer (CRC) care pathways. This study evaluates the management and outcomes of patients with primary locally advanced or recurrent CRC during the pandemic in a single tertiary referral centre.

methodsPatients undergoing elective surgery for advanced or recurrent CRC with curative intent between March 2020 and March 2021 were identified. Following first multidisciplinary team discussion patients were broadly classified into two groups: straight to surgery (

resultsForty-nine patients with a median age of 66 years (interquartile range: 54-73) were included. No patients developed a COVID-19 infection or related complication during hospital admission. Significant delays were identified in the treatment pathway of patients in the straight to surgery group, mostly due to delays in referral from external centres. Nine of 22 patients in the straight to surgery group had evidence of tumour progression compared with 3 of 27 in the neoadjuvant group (

conclusionThis study suggests that it is possible to mitigate the risks of COVID-19-related complications in patients undergoing complex surgery for locally advanced and recurrent CRC. Delay in surgical intervention is associated with tumour progression, particularly in patients who may not have neoadjuvant therapy. Efforts should be made to prioritise resources for patients requiring time-sensitive surgery for advanced and recurrent CRC.

Indexed as

Colorectal NeoplasmsCOVID-19AgedHumansNeoadjuvant TherapyNeoplasm Recurrence, LocalPandemicsAdvanced colorectal cancerCOVID-19Recurrent colorectal cancerSurgery

Identifiers

PMID35132892
PMCPMC9433197

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.