Evidence map›Paper›PMID 40422515›Full record

SynthesisCurrent oncology (Toronto, Ont.)2025

Minimally Invasive Surgical Techniques for Renal Cell Carcinoma with Intravenous Tumor Thrombus: A Systematic Review of Laparoscopic and Robotic-Assisted Approaches.

Yiting Wu, Shuyang Feng, Ping Fu

Abstract readSystematic Review
In one paragraph

Synthesis in Current oncology (Toronto, Ont.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yiting WuDepartment of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.
Shuyang FengDepartment of Urology, West China Hospital, Sichuan University, Chengdu 610041, China.
Ping FuDepartment of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLocally advanced renal cell carcinoma (RCC) with intravenous tumor thrombus (IVTT) represents 4-10% of renal tumors. This review assesses the safety and outcomes of minimally invasive techniques, specifically laparoscopic (LAP) and robotic-assisted (RA) methods, for treating RCC with IVTT.

methodsA literature search across several databases identified 54 studies (42 case series, 12 cohort studies) for analysis. Perioperative outcomes, including operative time, blood loss, transfusion rates, length of stay, and complications, were compared based on IVTT levels.

resultsLAP and RA techniques were feasible for low-level IVTT, showing similar perioperative results. RA outperformed LAP in high-level IVTT with shorter operative times and lower blood loss and transfusion rates, despite managing more complex cases. RA maintained stable cancer-specific mortality (CSM) and metastasis rates, whereas LAP exhibited higher rates in high-level cases. Both techniques had low local recurrence rates.

conclusionRA may be a superior option for RCC with IVTT, especially in high-level cases, but the data come mainly from specialized centers, signaling a need for multicenter validation and standardized criteria. Long-term outcomes require further study to assess RA's non-inferiority to LAP.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsLaparoscopyMinimally Invasive Surgical ProceduresRobotic Surgical ProceduresHumansintravenous tumor thrombus (IVTT)laparoscopic surgeryminimally invasive surgeryoncological safetyrenal cell carcinoma (RCC)robotic-assisted surgerysystematic review

Identifiers

PMID40422515
PMCPMC12109617

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.