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Impact of the preoperative modified Glasgow Prognostic Score on disease outcome after radical cystectomy for urothelial carcinoma of the bladder

2022· article· en· W3169170857 on OpenAlexaff
Victor M. Schuettfort, Kilian M. Gust, David D’Andrea, Fahad Quhal, Hadi Mostafaei, Ekaterina Laukhtina, Keiichiro Mori, Michael Rink, Mohammad Abufaraj, Pierre I. Karakiewicz, Stefano Luzzago, Morgan Rouprêt, Dmitry Enikeev, Kristin Zimmermann, Marina Deuker, Marco Moschini, Reza Sari Motlagh, Nico C. Grossmann, Satoshi Katayama, Benjamin Pradère, Shahrokh F. Shariat

Bibliographic record

VenueMinerva Urology and Nephrology · 2022
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineCystectomyReceiver operating characteristicLogistic regressionProportional hazards modelInternal medicineBladder cancerUrologyLymph nodeLymphovascular invasionArea under the curveCarcinomaGastroenterologyOncologyMetastasisCancer

Abstract

fetched live from OpenAlex

BACKGROUND: To investigate the predictive and prognostic value of the preoperative modified Glasgow Prognostic Score (mGPS) in patients with urothelial carcinoma of the bladder (UCB) treated with radical cystectomy (RC). METHODS: We conducted a retrospective analysis of an established multicenter database consisting of 4335 patients who were treated with RC±adjuvant chemotherapy for UCB between 1979 and 2012. The mGPS of each patient was calculated on the basis of preoperative serum C-reactive protein and albumin. Uni- and multivariable logistic and Cox regression analyses were performed. The discriminatory ability of the models was assessed by calculating the area under receiver operating characteristics curves (AUC) and concordance-indices (C-Index). The additional clinical net-benefit was assessed using the decision curve analysis (DCA). RESULTS: A mGPS of 0, 1, and 2 was observed in 3,158 (72.8%), 1,020 (23.5%), and 157 (3.6%) patients, respectively. On multivariable logistic regression analyses, mGPS of 1 or 2 were associated with an increased risk of pT3/4 disease at RC (OR 1.25, P=0.004 and OR 2.58, SP<0.001, respectively) and/or lymph node metastasis (OR 1.7, P<0.001 and OR 3.9, P<0.001, respectively). Addition of the mGPS to a predictive model based on preoperatively available variables improved its accuracy for prediction of lymph node metastasis (change of AUC +3.7%, P<0.001). On multivariable Cox regression analyses, mGPS of 1 or 2 remained associated with worse recurrence-free survival (HR 1.14, P=0.03 and HR 1.89 P<0.001, respectively), cancer-specific survival (HR 1.16, P=0.032 and HR 2.1, P<0.001, respectively) and overall survival (HR 1.5, P=0.007 and HR 1.92 P<0.001, respectively) compared to mGPS of 0. The additional discriminatory ability of the mGPS for prognosis of survival outcomes in separate models that included either established pre- or postoperative variables did not improve the C-Index by a prognostically relevant degree (change of C-Index <2% for all models). On DCA, the inclusion of the mGPS did not meaningfully improve the net-benefit for clinical decision-making regarding survival outcomes. CONCLUSIONS: We confirmed that an elevated mGPS is an independent risk factor for non-organ confined disease and poor survival outcomes in patients with UCB undergoing RC. However, the mGPS showed little value in improving the discriminatory ability of predictive and prognostic models that relied on either pre- or postoperative clinicopathological variables. The discriminatory ability of this biomarker in the age of immunotherapy warrants further evaluation.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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

Labeled directly by 2 models reading the full record.

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".

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Citations13
Published2022
Admission routes1
Has abstractyes

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