Evidence map›Paper›PMID 34778047›Full record

ArticleFrontiers in oncology2021

Economic Evaluation of Sacituzumab Govitecan for the Treatment of Metastatic Triple-Negative Breast Cancer in China and the US.

Jigang Chen, Mingyang Han, Aihua Liu, Bo Shi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 13% 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.

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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

4 authors at 4 institutions in 1 country.

Jigang ChenBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Mingyang HanDepartment of Neurosurgery, The Third Xiangya Hospital, Central South University, Changsha, China.
Aihua LiuBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Bo ShiDepartment of Breast Surgery, People's Hospital of Qinghai Province, Xining, China.
Beijing Tian Tan Hospital · CNCapital Medical University · CNQinghai No.3 People's Hospital · CNThird Xiangya Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe effectiveness of Sacituzumab Govitecan (SG) for metastatic triple-negative breast cancer (mTNBC) has been demonstrated. We aimed to evaluate its cost-effectiveness on mTNBC from the Chinese and United States (US) perspective.

methodsA partitioned survival model was developed to compare the cost and effectiveness of SG

resultsIn China, SG yielded an additional 0.35 quality-adjusted life-year (QALY) at an additional cost of Chinese Renminbi ¥2257842. The ICER was ¥6375856 ($924037)/QALY. In the US, SG yielded the same additional QALY at an extra cost of $175393 and the ICER was $494479/QALY. Similar results were obtained from the Markov model. One-way sensitivity analyses showed that SG price had the greatest impact on the ICER. PSA showed the probability of SG to be cost-effective when compared with chemotherapy was zero at the current willing-to-pay threshold of ¥217341/QALY and $150000/QALY in China and the US, respectively. The probability of cost-effectiveness of SG would approximate 50% if its price was reduced to ¥10.44/mg in China and $3.65/mg in the US.

conclusionSG is unlikely to be a cost-effective treatment of mTNBC at the current price both in China and the US.

Indexed as

breast cancerChinaeconomic evaluationSacituzumab GovitecanUS

Identifiers

PMID34778047
PMCPMC8581633
OpenAlexW3209673245

What OpenQuestion holds

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LicenceCC BY
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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.