Evidence map›Paper›PMID 33057024›Full record

ArticleScientific reports2020

A critical evaluation of visual proportion of Gleason 4 and maximum cancer core length quantified by histopathologists.

Lina Maria Carmona Echeverria, Aiman Haider, Alex Freeman, Urszula Stopka-Farooqui, Avi Rosenfeld, Benjamin S Simpson, Yipeng Hu, David Hawkes, Hayley Pye, Susan Heavey and 22 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 29% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

32 authors at 14 institutions in 2 countries.

Lina Maria Carmona EcheverriaMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK. l.echeverria@ucl.ac.uk.
Aiman HaiderDepartment of Pathology, University College London Hospital, 60 Whitfield Street, London, W1T4EU, UK.
Alex FreemanDepartment of Pathology, University College London Hospital, 60 Whitfield Street, London, W1T4EU, UK.
Urszula Stopka-FarooquiMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Avi RosenfeldDepartment of Computer Science, Jerusalem College of Technology, Havaad Haleumi 21, Givat Mordechai, 91160, Jerusalem, Israel.
Benjamin S SimpsonMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Yipeng HuCentre for Medical Image Computing, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
David HawkesCentre for Medical Image Computing, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Hayley PyeMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Susan HeaveyMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Vasilis StavrinidesMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Joseph M NorrisMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Ahmed El-Shater BosailyDivision of Surgery and Interventional Science, Department of Urology, University College London Hospital, 235 Euston Road, London, NW1 2BU, UK.
Cristina Cardona BarrenaMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Simon BottDepartment Urology, Frimley Park Hospital, Frimley Health NHS Foundation Trust, Portsmouth Road, Camberley, Surrey, GU16 7UJ, UK.
Louise BrownMRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ, UK.
Nick Burns-CoxDepartment of Urology, Musgrove Park Hospital, Taunton and Somerset NHS Foundation Trust, Taunton, TA1 5DA, UK.
Tim DudderidgeDepartment of Urology, University Hospital Southampton NHS Foundation Trust, Tremona Road, Southampton, Hampshire, SO16 6YD, UK.
Alastair HendersonDepartment of Urology, Maidstone and Tunbridge Wells NHS Trust, Hermitage Lane, Tunbridge Wells, ME16 9QQ, UK.
Richard HindleyDepartment of Urology, Hampshire Hospitals NHS Foundation Trust, Aldermaston Road, Basingstoke, Hampshire, RG24 9NA, UK.
Richard KaplanMRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ, UK.
Alex KirkhamCentre for Medical Image Computing, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Robert OldroydPublic and Patient Representative, 19 Exbury Gardens, West Bridgford, Nottingham, NG2 7SL, UK.
Maneesh GheiDepartment of Urology, Whittington Health NHS Trust, Magdala Avenue, London, N19 5NF, UK.
Raj PersadDepartment of Urology, North Bristol NHS Trust, Southmead Road, Westbury-on-Trym, Bristol, BS10 5NB, UK.
Shonit PunwaniCentre for Medical Image Computing, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
Derek RosarioDepartment of Urology, Sheffield Teaching Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, Glossop Road, Sheffield, South Yorkshire, S10 2JF, UK.
Iqbal ShergillDepartment of Urology, Wrexham Maelor Hospital NHS Trust, Croesnewydd Road, Wrexham, LL13 7TD, UK.
Mathias WinklerDepartment of Urology, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Hashim U AhmedDepartment of Urology, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Mark EmbertonDivision of Surgery and Interventional Science, Department of Urology, University College London Hospital, 235 Euston Road, London, NW1 2BU, UK.
Hayley C WhitakerMolecular Diagnostics and Therapeutics Group, Division of Surgery and Interventional Science, University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
University College London · GBUniversity College Hospital · GBImperial College London · GBMRC Clinical Trials Unit at UCL · GBFrimley Health NHS Foundation Trust · GBHampshire Hospitals NHS Foundation Trust · GBJerusalem College of Technology · ILMaidstone and Tunbridge Wells NHS Trust · GBMusgrove Park Hospital · GBNorth Bristol NHS Trust · GBRoyal Hallamshire Hospital · GBUniversity Hospital Southampton NHS Foundation Trust · GBWhittington Health NHS Trust · GBWrexham Maelor Hospital · GB

Funding

Medical Research Council MC_EX_UU_G0800814Medical Research Council MC_UU_12023/20Medical Research Council MC_UU_12023/28Medical Research Council MC_UU_12023/6Medical Research Council MR/S005897/1Medical Research Council MR/S00680X/1Prostate Cancer UK CEO13_2-002Prostate Cancer UK PG14-018-TR2Wellcome Trust 204998/Z/16/Z
6 · The paper itself

Abstract

Gleason score 7 prostate cancer with a higher proportion of pattern 4 (G4) has been linked to genomic heterogeneity and poorer patient outcome. The current assessment of G4 proportion uses estimation by a pathologist, with a higher proportion of G4 more likely to trigger additional imaging and treatment over active surveillance. This estimation method has been shown to have inter-observer variability. Fifteen patients with Prostate Grade Group (GG) 2 (Gleason 3 + 4) and fifteen patients with GG3 (Gleason 4 + 3) disease were selected from the PROMIS study with 192 haematoxylin and eosin-stained slides scanned. Two experienced uropathologists assessed the maximum cancer core length (MCCL) and G4 proportion using the current standard method (visual estimation) followed by detailed digital manual annotation of each G4 area and measurement of MCCL (planimetric estimation) using freely available software by the same two experts. We aimed to compare visual estimation of G4 and MCCL to a pathologist-driven digital measurement. We show that the visual and digital MCCL measurement differs up to 2 mm in 76.6% (23/30) with a high degree of agreement between the two measurements; Visual gave a median MCCL of 10 ± 2.70 mm (IQR 4, range 5-15 mm) compared to digital of 9.88 ± 3.09 mm (IQR 3.82, range 5.01-15.7 mm) (p = 0.64) The visual method for assessing G4 proportion over-estimates in all patients, compared to digital measurements [median 11.2% (IQR 38.75, range 4.7-17.9%) vs 30.4% (IQR 18.37, range 12.9-50.76%)]. The discordance was higher as the amount of G4 increased (Bias 18.71, CI 33.87-48.75, r 0.7, p < 0.0001). Further work on assessing actual G4 burden calibrated to clinical outcomes might lead to the use of differing G4 thresholds of significance if the visual estimation is used or by incorporating semi-automated methods for G4 burden measurement.

Indexed as

AdultAgedAged, 80 and overHumansMaleMiddle AgedNeoplasm GradingObserver VariationPathologistsProstateProstatic Neoplasms

Identifiers

PMID33057024
PMCPMC7561724
OpenAlexW3093136879

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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.