Evidence map›Paper›PMID 32859659›Full record

SynthesisBMJ open2020

What is the optimum systemic treatment for advanced/metastatic renal cell carcinoma of favourable, intermediate and poor risk, respectively? A systematic review and network meta-analysis.

Guanghui Cao, Xiaoqiang Wu, Zhiwei Wang, Xiangyong Tian, Chan Zhang, Xuan Wu, Haotian Zhang, Gaopeng Jing, Tianzhong Yan

Open access · goldAbstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 12% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. 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

9 authors at 1 institution in 1 country.

Guanghui CaoDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Xiaoqiang WuDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Zhiwei WangDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Xiangyong TianDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Chan ZhangDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Xuan WuDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Haotian ZhangDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Gaopeng JingDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
Tianzhong YanDepartment of Urology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China ytz460@hotmail.com.ORCID 0000-0002-0275-5533
Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe optimum systemic therapies for advanced/metastatic renal cell carcinoma (RCC) of favourable, intermediate and poor risk have not been established. We aimed to compare and rank the effects associated with systemic therapies in the first-line setting.

methodsWe searched PubMed, Cochrane databases, Web of Science and ClinicalTrials.gov for randomised controlled trials (RCT) published up to February 2020 of all available treatments for advanced/metastatic RCC. Analysis was done on a Bayesian framework.

results15 unique RCTs including 8995 patients were identified. For advanced/metastatic RCC of favourable risk, avelumab plus axitinib was associated with a significantly higher improvement in progression-free survival (PFS) than sunitinib (HR 0.57, 95% CI 0.34 to 0.96). For intermediate-risk patients, cabozantinib, nivolumab plus ipilimumab, pembrolizumab plus axitinib and avelumab plus axitinib were associated with significantly higher improvement in PFS than sunitinib (HR 0.63, 95% CI 0.44 to 0.97; HR 0.66, 95% CI 0.53 to 0.81; HR 0.58, 95% CI 0.44 to 0.80; HR 0.62, 95% CI 0.47 to 0.83, respectively); pembrolizumab plus axitinib and nivolumab plus ipilimumab were associated with significantly higher improvement in overall survival (OS) than sunitinib (HR 0.53, 95% CI 0.34 to 0.81; HR 0.66, 95% CI 0.50 to 0.87, respectively). For poor-risk patients, nivolumab plus ipilimumab and pembrolizumab plus axitinib were associated with significantly higher improvement in PFS than sunitinib (HR 0.57, 95% CI 0.43 to 0.76; HR 0.48, 95% CI 0.30 to 0.82, respectively); nivolumab plus ipilimumab and pembrolizumab plus axitinib were significantly more efficacious for OS than sunitinib (HR 0.57, 95% CI 0.39 to 0.883; HR 0.43, 95% CI 0.23 to 0.80, respectively). For OS, there were 81% and 78% probabilities that pembrolizumab plus axitinib was the best option for intermediate-risk and poor-risk patients, respectively.

conclusionAvelumab plus axitinib might be the optimum treatment for advanced/metastatic RCC of favourable risk. Pembrolizumab plus axitinib might be the optimum treatment for intermediate-risk and poor-risk patients.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsAxitinibHumansSunitinibAxitinibSunitinibimmunologykidney tumoursurological tumours

Identifiers

PMID32859659
PMCPMC7454197
OpenAlexW3080692347

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.