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Record W4297929300

Robotic Surgical System for Radical Prostatectomy: A Health Technology Assessment.

2017· article· en· W4297929300 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsProstatectomyMedicineProstate cancerLaparoscopic radical prostatectomyPerioperativeUrologyGeneral surgeryCancerSurgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Prostate cancer is the second most common type of cancer in Canadian men. Radical prostatectomy is one of the treatment options available, and involves removing the prostate gland and surrounding tissues. In recent years, surgeons have begun to use robot-assisted radical prostatectomy more frequently. We aimed to determine the clinical benefits and harms of the robotic surgical system for radical prostatectomy (robot-assisted radical prostatectomy) compared with the open and laparoscopic surgical methods. We also assessed the cost-effectiveness of robot-assisted versus open radical prostatectomy in patients with clinically localized prostate cancer in Ontario. METHODS: We performed a literature search and included prospective comparative studies that examined robot-assisted versus open or laparoscopic radical prostatectomy for prostate cancer. The outcomes of interest were perioperative, functional, and oncological. The quality of the body of evidence was examined according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also conducted a cost-utility analysis with a 1-year time horizon. The potential long-term benefits of robot-assisted radical prostatectomy for functional and oncological outcomes were also evaluated in a 10-year Markov model in scenario analyses. In addition, we conducted a budget impact analysis to estimate the additional costs to the provincial budget if the adoption of robot-assisted radical prostatectomy were to increase in the next 5 years. A needs assessment determined that the published literature on patient perspectives was relatively well developed, and that direct patient engagement would add relatively little new information. RESULTS: Compared with the open approach, we found robot-assisted radical prostatectomy reduced length of stay and blood loss (moderate quality evidence) but had no difference or inconclusive results for functional and oncological outcomes (low to moderate quality evidence). Compared with laparoscopic radical prostatectomy, robot-assisted radical prostatectomy had no difference in perioperative, functional, and oncological outcomes (low to moderate quality evidence). Compared with open radical prostatectomy, our best estimates suggested that robot-assisted prostatectomy was associated with higher costs ($6,234) and a small gain in quality-adjusted life-years (QALYs) (0.0012). The best estimate of the incremental cost-effectiveness ratio (ICER) was $5.2 million per QALY gained. However, if robot-assisted radical prostatectomy were assumed to have substantially better long-term functional and oncological outcomes, the ICER might be as low as $83,921 per QALY gained. We estimated the annual budget impact to be $0.8 million to $3.4 million over the next 5 years. CONCLUSIONS: There is no high-quality evidence that robot-assisted radical prostatectomy improves functional and oncological outcomes compared with open and laparoscopic approaches. However, compared with open radical prostatectomy, the costs of using the robotic system are relatively large while the health benefits are relatively small.

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)0.019
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.095
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0130.013
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.043
GPT teacher head0.337
Teacher spread0.295 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations44
Published2017
Admission routes1
Has abstractyes

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