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Record W1593849496 · doi:10.1111/bju.13212

Oncological control associated with surgical resection of isolated retroperitoneal lymph node recurrence of renal cell carcinoma

2015· article· en· W1593849496 on OpenAlexaff
Christopher Russell, Kathy Lue, John Fisher, Wassim Kassouf, Thomas Schwaab, Wade J. Sexton, Simon Tanguay, Sarah P. Psutka, R. Houston Thompson, Bradley C. Leibovich, Michael Hanzly, Philippe E. Spiess, Stephen A. Boorjian

Bibliographic record

VenueBritish Journal of Urology · 2015
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineNephrectomyRenal cell carcinomaInterquartile rangeSurgeryProportional hazards modelLymph nodeInternal medicineKidney

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the outcome of patients after surgical resection of isolated retroperitoneal lymph node (RPLN) recurrence of renal cell carcinoma (RCC) using a multicentre international cohort. PATIENTS AND METHODS: In all, 50 patients were identified who underwent resection of isolated RPLN recurrence of RCC at four institutions after nephrectomy for pTany Nany M0 disease. Progression-free (PFS) and cancer-specific survival (CSS) were estimated using the Kaplan-Meier method. Cox proportional hazards regression models were used to assess the association of clinicopathological characteristics with disease progression. RESULTS: The median (interquartile range, IQR) age at resection was 57.0 (50.0-62.5) years. The median (IQR) time to RPLN recurrence after nephrectomy was 12.6 (6.9-39.5) months, with no significant difference in median time to RPLN recurrence between patients with N+ disease at nephrectomy (10.7 [6.5-24.6] months) and those with Nx/pN0 disease at nephrectomy (13.7 [8.7-44.2] months) (P = 0.66). The median (IQR) size of the RPLN recurrence before resection was 2.6 (1.9-5) cm. The most common site for RPLN recurrence was within the interaortocaval region (34%). The median (IQR) follow-up after RPLN resection for patients alive at last follow-up was 28.0 (13.7-51.2) months. During follow-up, 26 patients developed RCC recurrence, at a median (IQR) of 9.9 (4.0-18.5) months after RPLN resection. Of those who developed a secondary recurrence, disease was again isolated to the retroperitoneum in seven patients. In all, 11 patients subsequently died, including 10 who died from disease. The median PFS after RPLN resection was 19.5 months, with a 3- and 5-year PFS of 40.5% and 35.4%, respectively. We also found that RPLN recurrence at ≤12 months after nephrectomy was associated with a significantly inferior median PFS (12.3 months) compared with RPLN recurrence at >12 months after nephrectomy (47.6 months; P = 0.003). Moreover, on multivariate analysis, a shorter time to recurrence remained associated with a significantly increased risk for subsequent disease progression (hazard ratio 3.51; P = 0.005). CONCLUSION: Surgical resection of isolated RPLN recurrence from RCC may result in durable cancer control in appropriately selected patients. Recurrence at ≤12 months after nephrectomy was associated with a significantly increased risk of progression after resection, underscoring the importance of this variable for risk stratification. Thus, we recommend that, in the setting of isolated RPLN recurrence of RCC (in patients without precluding comorbidities), careful consideration with the patients and medical oncology colleagues be undertaken about the relative and individualised benefits of surgical resection, systemic therapy, and surveillance.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.253
Teacher spread0.228 · 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".

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Citations21
Published2015
Admission routes1
Has abstractyes

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