Evidence map›Paper›PMID 36539696›Full record

ArticleBMC geriatrics2022

Efficacy of regorafenib combined with PD-1 inhibitors in elderly patients with advanced metastatic colorectal cancer.

Beibei Chen, Huichen Zhao, Jinxi Huang, Huifang Lv, Weifeng Xu, Caiyun Nie, Jianzheng Wang, Jing Zhao, Yunduan He, Saiqi Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 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

11 authors at 2 institutions in 1 country.

Beibei ChenDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Huichen ZhaoDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Jinxi HuangDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Huifang LvDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Weifeng XuDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Caiyun NieDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Jianzheng WangDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Jing ZhaoDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Yunduan HeDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Saiqi WangDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China.
Xiaobing ChenDepartment of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450008, Henan Province, China. zlyychenxb0807@zzu.edu.cn.
Zhengzhou University · CNHenan Cancer Hospital · CN

Funding

Medical Science and Technique Foundation of Henan Province LHGJ20210172Science and Technique Foundation of Henan Province 202102310121Science and Technique Foundation of Henan Province 212102310771the 1000 Talents Program of Central plains 204200510023
6 · The paper itself

Abstract

objectiveThis is the first clinical study that wants to investigate the treatment patterns, clinical outcomes, and prognostic factors of regorafenib plus PD-1 inhibitors therapy in Chinese elderly patients with advanced colorectal cancer.

methodsA cohort of metastatic colorectal cancer patients 60 years or older who received treatment with regorafenib combined with PD-1 inhibitors was included in our analysis. The endpoints included overall survival (OS), progression-free survival (PFS), and prognostic factors.

resultsIn total, 24 patients were enrolled with the median age of 68 years, and 62.5% were female. The median OS and PFS were 15.03 months (95% CI 7.0-23.0) and 4.0 months (95% CI 1.8-6.2), respectively. The objective response rate was 8.3%, and the disease control rate was 70.8%. Patients previously treated with regorafenib had a longer median PFS than those without (6.3 versus 2.8 months). In terms of final daily doses, it showed a trend toward better PFS (median PFS was 10.0 months) in high-dose group (daily dose above 80 mg of regorafenib) compared to low-dose group (daily dose no more than 80 mg of regorafenib) (median PFS was 3.5 months).

conclusionsThis real-world evidence confirms that Chinese elderly patients with advanced colorectal cancer may benefit from the treatment of regorafenib combined with PD-1 inhibitors, similarly with this combination therapy strategies in all age patients.

Indexed as

Colorectal NeoplasmsImmune Checkpoint InhibitorsAgedFemaleHumansMalePhenylurea CompoundsPyridinesImmune Checkpoint InhibitorsPhenylurea CompoundsPyridinesregorafenibColorectal cancerElderly patientsImmunotherapyProgrammed cell death protein 1Regorafenib

Identifiers

PMID36539696
PMCPMC9769053
OpenAlexW4313279992

What OpenQuestion holds

Textmetadata
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.