Evidence map›Paper›PMID 34538077›Full record

ArticleThe British journal of radiology2022

Serial changes in tumour measurements and apparent diffusion coefficients in prostate cancer patients on active surveillance with and without histopathological progression.

Nikita Sushentsev, Iztok Caglic, Leonardo Rundo, Vasily Kozlov, Evis Sala, Vincent J Gnanapragasam, Tristan Barrett

Abstract read
In one paragraph

Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Innovations in prostate cancer: introductory editorial.The British journal of radiology · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Nikita SushentsevDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
Iztok CaglicDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
Leonardo RundoDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
Vasily KozlovDepartment of Public Health and Healthcare Organisation, Sechenov First Moscow State Medical University, Moscow, Russia.
Evis SalaDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
Vincent J GnanapragasamDivision of Urology, Department of Surgery, University of Cambridge, Cambridge, UK.
Tristan BarrettDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.

Funding

Cancer Research UK 28667
6 · The paper itself

Abstract

objectiveTo analyse serial changes in MRI-derived tumour measurements and apparent diffusion coefficient (ADC) values in prostate cancer (PCa) patients on active surveillance (AS) with and without histopathological disease progression.

methodsThis study included AS patients with biopsy-proven PCa with a minimum of two consecutive MR examinations and at least one repeat targeted biopsy. Tumour volumes, largest axial two-dimensional (2D) surface areas, and maximum diameters were measured on

results60 patients (30 progressors and 30 non-progressors) were included. In progressors,

conclusionAS patients show significant differences in tumour measurements and ADC values between those with and without histopathological disease progression. ADVANCES IN KNOWLEDGE: This paper proposes specific clinical cut-offs for

Indexed as

Tumor BurdenWatchful WaitingAgedBiopsyDiffusion Magnetic Resonance ImagingDisease ProgressionHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedProstatic NeoplasmsRetrospective Studies

Identifiers

PMID34538077
PMCPMC8978242

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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.