Evidence map›Paper›PMID 42333973›Full record

ArticleAmerican journal of hematology2026

A Multicenter National Study of AL Amyloidosis in China: Insights Into Real-World Diagnosis, Treatment, and Prognosis.

Jing Li, Chenqi Yu, Jinghua Wang, Ning An, Yujun Dong, Lijuan Chen, Jun Luo, Sili Wang, Quanyi Lu, Songfu Jiang and 21 more

Abstract readMulticenter Study
In one paragraph

Article in American journal of hematology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

31 authors.

Jing LiDepartment of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China.
Chenqi YuDepartment of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China.
Jinghua WangDepartment of Hematology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Ning AnDepartment of Hematology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yujun DongDepartment of Hematology, First Hospital of Peking University, Beijing, China.
Lijuan ChenDepartment of Hematology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.ORCID https://orcid.org/0000-0002-6497-1194
Jun LuoDepartment of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Sili WangDepartment of Hematology, Zhongshan Hospital, Xiamen University, Xiamen, Fujian, China.ORCID https://orcid.org/0000-0003-4886-9226
Quanyi LuDepartment of Hematology, Zhongshan Hospital, Xiamen University, Xiamen, Fujian, China.
Songfu JiangDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, China.
Jin ZhangDepartment of Hematology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China.
Yong ZouDepartment of Hematology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China.
Lihong ShouDepartment of Hematology, Huzhou Central Hospital, Affiliated Central Hospital HuZhou University, Zhejiang, China.
Lin ShenDepartment of Hematology, Huadong Hospital, Fudan University, Shanghai, China.
Junmin ChenDepartment of Hematology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Li ZhangDepartment of Hematology, Taizhou Hospital of Zhejiang Province, Zhejiang, China.
Xuzhang LuDepartment of Hematology, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, China.
Jia FengDepartment of Hematology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Hongyu ZhangDepartment of Hematology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Huifang JiangDepartment of Hematology, Tongde Hospital of Zhejiang Province, Zhejiang, China.
Jihao ZhouDepartment of Hematology, Shenzhen People's Hospital (the Second Clinical Medical College, Jinan University; the First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-2684-192X
Tianhong XuDepartment of Hematology, Shanghai Geriatric Medical Center (Zhongshan Hospital Fudan University Minhang Campus), Shanghai, China.
Wenjing WangDepartment of Hematology, Shanghai Geriatric Medical Center (Zhongshan Hospital Fudan University Minhang Campus), Shanghai, China.
Yang YangDepartment of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China.
Fanjie ZhouDepartment of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China.
Weiwei XieDepartment of Hematology, First Hospital of Peking University, Beijing, China.
Xuxing ShenDepartment of Hematology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Yang YangDepartment of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Peilong LaiDepartment of Hematology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Chunrui LiDepartment of Hematology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID https://orcid.org/0000-0001-5134-7133
Peng LiuDepartment of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID https://orcid.org/0000-0002-9639-6606

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This national, multicenter, retrospective study analyzed 1070 patients with newly diagnosed systemic light-chain (AL) amyloidosis in China (2008-2025). Findings reveal increasing annual diagnoses and a marked shift in first-line therapy from proteasome inhibitor (PI)-based regimens to predominantly daratumumab-based regimens since 2024. Monthly kinetic assessments demonstrated that daratumumab-based induction produced deeper and faster hematologic responses than PI-based therapy [≥ very good hematologic partial response (HemVGPR): 80.3% vs. 70.8%, p = 0.012; median time to ≥ HemVGPR: 1.2 vs. 1.8 months, p = 0.001], with significantly superior cardiac overall response (63.1% vs. 53.3%, p = 0.030). Early mortality rates at 1, 3, and 6 months were 5.5%, 13.2%, and 16.2%, respectively, with daratumumab-based therapy identified as an independent protective factor for 6-month mortality. Median event-free survival (EFS) was 44.4 months, while median overall survival (OS) was not reached. Achievement of hematologic complete response (HemCR) conferred superior EFS and OS over HemVGPR (both p < 0.001), with minimal residual disease negativity further improving EFS in HemCR patients (p = 0.043). Concurrent hepatic and cardiac involvement defined a high-risk subgroup with poor outcomes (median EFS 12.8 months, OS 51.0 months). Multivariable analysis confirmed Eastern Cooperative Oncology Group (ECOG) performance status (PS) > 2, liver involvement, and gain1q as adverse prognostic factors for EFS, whereas ≥ HemVGPR was protective. For OS, liver involvement, concomitant multiple myeloma, and ECOG PS > 2 were independent risk factors, while ≥ HemVGPR and cardiac response predicted improved survival. This study establishes a contemporary benchmark for AL amyloidosis management in China, confirming the superior real-world efficacy of daratumumab-based frontline therapy.

Indexed as

Antibodies, MonoclonalImmunoglobulin Light-chain AmyloidosisAdultAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedPrognosisProteasome InhibitorsRetrospective StudiesSurvival RateAntibodies, MonoclonaldaratumumabProteasome Inhibitorsdaratumumabimmunoglobulin light‐chain amyloidosisprognosis

Identifiers

PMID42333973
PMCPMC13428378

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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.