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Record W2267025725 · doi:10.5489/cuaj.61

Collaborations in renal cell carcinoma research

2012· article· en· W2267025725 on OpenAlexaffvenueabout
Lori Wood, Michael A.S. Jewett

Bibliographic record

VenueCanadian Urological Association Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsCanadian Urological Association
Fundersnot available
KeywordsRenal cell carcinomaMedicineTemsirolimusSunitinibSorafenibDiseaseMalignancyInternal medicineBiology

Abstract

fetched live from OpenAlex

Welcome to the first supplement of the Canadian Urological Association Journal. As editors of this inaugural supplement, we are excited to present the most up-to-date information about renal cell carcinoma, written by respected Canadian and international physicians, surgeons and investigators. The explosion of information about molecular genetics, surgical management and targeted systemic therapy made renal cell carcinoma an obvious choice of topic for this supplement. The incidence of this disease is increasing by 2%–3% each year, and more people are being diagnosed at an earlier stage. The cause of the disease is unknown, but more is known about its tumour genetics than any other common genitourinary malignancy. Applying new molecular techniques to characterize individual tumours is now a real possibility, as is understanding why some tumours progress and some are more sensitive to the targeted therapies that have recently become widely available. These advances have brought new enthusiasm, integrated science and multidisciplinary collaboration to the management of patients with renal cell carcinoma. As a direct result of these advances, our patients' prognosis has improved, and all disciplines have a renewed commitment to continue striving for further advancements. Collaboration among basic scientists, urologists, medical oncologists, medical imagers and pathologists in research and management continues to develop and prosper. It is this collaboration that we celebrate in this supplement. The supplement highlights key aspects of renal cell carcinoma, from its molecular genetics and molecular characterization to a review of immunotherapy and an overview of new systemic therapies, including sunitinib, sorafenib and temsirolimus, to advances in surgery for local and advanced kidney cancer. Future directions for the management of renal cell carcinoma in Canada and the collaboration that this will entail are also highlighted in the supplement. It also raises questions about current optimal first-line and second-line therapies and methods of integrating cytoreductive surgery into the overall management of metastatic renal cell carcinoma in an era of targeted therapy. Also raised are more global and societal issues such as how these new therapies will be paid for in a public healthcare system and what will happen to our patients if the public healthcare system decides not to fund them. We would like to take this opportunity to inform our readers about the phase 3 adjuvant clinical trial for patients with localized renal cell carcinoma, sponsored by the National Cancer Institute of Canada. This clinical trial will study patients with an intermediate or high risk of relapse after nephrectomy (pT1B grade 3 or 4 and above, up to node-positive disease) and randomize patients to sunitinib, sorafenib or placebo groups for 1 year. The hope is that improvements in systemic therapy for metastatic disease will translate into a survival benefit for patients who have resected local disease. Patients can be randomized either before or after nephrectomy. Canada can make a real contribution to this research by accruing patients to this study. We hope that all Canadian centres will participate in this exciting clinical trial. Should you need further information, please do not hesitate to contact either of us. Happy reading and learning!

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)0.009
metaresearch head score (Gemma)0.043
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.120
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0050.002
Scholarly communication0.0110.006
Open science0.0020.006
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.1200.042

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 head0.061
GPT teacher head0.296
Teacher spread0.235 · 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

Citations0
Published2012
Admission routes3
Has abstractyes

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