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Record W4400720534 · doi:10.1016/j.euo.2024.07.003

Has Active Surveillance for Prostate Cancer Become Safer? Lessons Learned from a Global Clinical Registry

2024· article· en· W4400720534 on OpenAlexaff
Chris H. Bangma, Paul Doan, Lin Zhu, Sebastiaan Remmers, Daan Nieboer, Jozien Helleman, Monique J. Roobol, Mikio Sugimoto, Byung Ha Chung, Lui Shiong Lee, Mark Frydenberg, Laurence Klotz, Michael Peacock, Antoinette S. Perry, Anders Bjartell, Antti Rannikko, Mieke Van Hemelrijck, Prokar Dasgupta, Caroline M. Moore, Bruce J. Trock, Christian P. Pavlovich, Ewout W. Steyerberg, Peter R. Carroll, Kyo Chul Koo, Andrew Hayen, James Thompson

Bibliographic record

VenueEuropean Urology Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsSunnybrook Health Science CentreUniversity of British ColumbiaHealth Sciences CentreBC Cancer AgencyUniversity of Toronto
FundersMovember Foundation
KeywordsSAFERMedicineProstate cancerMedical physicsCancerInternal medicineComputer securityComputer science

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Active surveillance (AS) has evolved into a widely applied treatment strategy for many men around the world with low-risk prostate cancer (or in selected cases intermediate-risk disease). Here, we report on the safety and acceptability of AS, and treatment outcomes for low- and intermediate-risk tumours over time in 14 623 men with follow-up of over 6 yr. METHODS: Clinical data from 26 999 men on AS from 25 cohorts in 15 countries have been collected in an international database from 2000 onwards. KEY FINDINGS AND LIMITATIONS: Across our predefined four time periods of 4 yr each (covering the period 2000-2016), there was no significant change in overall survival (OS). However, metastasis-free survival (MFS) rates have improved since the second period and were excellent (>99%). Treatment-free survival rates for earlier periods showed a slightly more rapid shift to radical treatment. Over time, there was a constant proportion of 5% of men for whom anxiety was registered as the reason for treatment alteration. There was, however, also a subset of 10-15% in whom treatment was changed, for which no apparent reason was available. In a subset of men (10-15%), tumour progression was the trigger for treatment. In men who opted for radical treatment, surgery was the most common treatment modality. In those men who underwent radical treatment, 90% were free from biochemical recurrence at 5 yr after treatment. CONCLUSIONS AND CLINICAL IMPLICATIONS: Our study confirms that AS was a safe management option over the full duration in this large multicentre cohort with long-term follow-up, given the 84.1% OS and 99.4% MFS at 10 yr. The probability of treatment at 10 yr was 20% in men with initial low-risk tumours and 31% in men with intermediate-risk tumours. New diagnostic modalities may improve the acceptability of follow-up using individual risk assessments, while safely broadening the use of AS in higher-risk tumours. PATIENT SUMMARY: Active surveillance (AS) has evolved into a widely applied treatment strategy for many men with prostate cancer around the world. In this report, we show the long-term safety of following AS for men with low- and intermediate-risk prostate cancer. Our study confirms AS as a safe management option for low- and intermediate-risk prostate cancer. New diagnostic modalities may improve the acceptability of follow-up using individual risk assessments, while safely broadening the use of AS in higher-risk tumours.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.063
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.085
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.002
Scholarly communication0.0050.008
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.127
GPT teacher head0.428
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2024
Admission routes1
Has abstractyes

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