Evidence map›Paper›PMID 35800045›Full record

ArticleFrontiers in oncology2022

Cost-Effectiveness of Lenvatinib Plus Pembrolizumab or Everolimus as First-Line Treatment of Advanced Renal Cell Carcinoma.

Ye Wang, Hao Wang, Manman Yi, Zhou Han, Li Li

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
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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

5 authors.

Ye WangNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, China.
Hao WangDepartment of Pharmacy, Drum Tower Hospital Affiliated to Medical School of Nanjing University, Nanjing, China.
Manman YiNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, China.
Zhou HanDepartment of Pharmacy, Drum Tower Hospital Affiliated to Medical School of Nanjing University, Nanjing, China.
Li LiDepartment of Pharmacy, Drum Tower Hospital Affiliated to Medical School of Nanjing University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In this study, compared to sunitinib as one of the available treatment options, we aimed to evaluate the cost-effectiveness of lenvatinib plus pembrolizumab or everolimus as first-line treatment for advanced renal cell carcinoma (RCC) patients in a Chinese health system setting. Methods: A partitioned survival model was developed to simulate patient disease and death. Transition probabilities and adverse reaction data were obtained from the CLEAR trial. The utility value was derived from literature. Costs were based on the Chinese drug database and local charges. Sensitivity analyses and were performed to assess the robustness of the model. Outcomes were measured as quality-adjusted life-years (QALYs), cumulative cost (COST), and incremental cost-effectiveness ratio (ICER). Results: The model predicted that the expected mean result in the lenvatinib plus pembrolizumab group (2.60 QALYs) was superior to that in the sunitinib group (2.13 QALYs) to obtain 0.47 QALYs, but the corresponding cost was 1,253,130 yuan greater, resulting in an ICER of 2,657,025 RMB/QALYs. Compared with the sunitinib group, the lenvatinib plus everolimus group (2.17 QALYs) gained 0.04 QALYs, with an additional cost of 32,851 yuan, resulting in an ICER of 77,6202 RMB/QALYs. Conclusions: Lenvatinib plus pembrolizumab or everolimus has no economic advantage over sunitinib in treating advanced RCC in the Chinese healthcare system.

Indexed as

cost-effectivenesslenvatinibpartitioned survivalpembrolizumabrenal cell carcinoma

Identifiers

PMID35800045
PMCPMC9254865

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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.