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Does patient age affect survival after radical cystectomy?

2012· article· en· W1942424277 on OpenAlexaffabout
David Horovitz, Polat Türker, Peter J. Boström, Tuomas Mirtti, Martti Nurmi, Cynthia Kuk, Girish S. Kulkarni, Neil Fleshner, Antonio Finelli, Michael A.S. Jewett, Alexandre R. Zlotta

Bibliographic record

VenueBritish Journal of Urology · 2012
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsMount Sinai HospitalPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsCystectomyMedicineBladder cancerComorbidityGenitourinary systemPathologicalAffect (linguistics)PopulationScrutinyIntensive care medicineInternal medicineCancerPsychology

Abstract

fetched live from OpenAlex

UNLABELLED: What's known on the subject? and What does the study add? Elderly patients have more years to compound comorbidities and it has previously been shown that comorbidity is an important predictor of overall survival in patients with bladder cancer, including those treated with radical cystectomy (RC). Other studies have also demonstrated higher stage at diagnosis, higher rate of upstaging on final pathology and a longer delay to definitive therapy for older patients. Because of these findings, elderly patients are being offered RC less often than younger patients. Whether or not this practice is justified has come under recent scrutiny and there has been much conflicting data in the literature. While some studies have shown worse outcomes for elderly patients, others have shown similar results for both elderly and younger patients. Large population-based databases have recently been used to try to determine whether age effects outcome after RC but their conclusions may not be as generalizable as ours for several reasons: billing code data was used to build patient cohorts, patients were generally recipients of Medicare, lack of pathological review, and lack of available and accurate clinical data. Our series is unique in that it comprises a large group of patients from two major tertiary care academic institutions using a very robust dataset. Pathological specimens were reviewed by dedicated genitourinary pathologists, including those recovered from peripheral hospitals. Our sample size is one of the largest single- or multi-institutional studies. OBJECTIVE: • To analyse the impact of patient age on survival after radical cystectomy (RC). PATIENTS AND METHODS: • After ethics review board approval, two databases of patients with bladder cancer (BC) undergoing RC at the University Heath Network, Toronto, Canada (1992-2008) and the University of Turku, Turku, Finland (1986-2005) were retrospectively analysed. • A total of 605 patients who underwent this procedure between June 1985 and March 2010 were included. • Patients were divided into four age groups: ≤ 59, 60-69, 70-79 and ≥ 80 years. • Demographic, clinical and pathological data were compared, as well as recurrence-free survival (RFS), disease-specific survival (DSS) and overall survival (OAS) rates. RESULTS: • Compared with younger patients (age ≤ 79 years), elderly patients (age ≥ 80 years) had higher American Society of Anesthesiologists scores (P < 0.001), a greater number of lymph nodes removed during surgical dissection (P < 0.001), and underwent less adjuvant treatment (P < 0.001). • Choice of urinary diversion differed among the groups, with ileal conduit being used for all patients ≥ 80 years (P < 0.001). • No differences were noted between age groups with respect to RFS (P= 0.3), DSS (P= 0.4) or OAS (P= 0.4). CONCLUSION: • Although RC is an operation with significant morbidity, it is a viable treatment option for carefully selected elderly patients. Senior patients (≥ 80 years) should not be denied RC if they are deemed fit to undergo surgery. • Senior adults do not suffer from adverse histopathological features as compared with younger patients.

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)0.002
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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

Citations38
Published2012
Admission routes2
Has abstractyes

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