Evidence map›Paper›PMID 35372057›Full record

ArticleFrontiers in oncology2022

Development and Validation of a Novel Prognostic Model for Overall Survival in Newly Diagnosed Multiple Myeloma Integrating Tumor Burden and Comorbidities.

Shuangshuang Jia, Lei Bi, Yuping Chu, Xiao Liu, Juan Feng, Li Xu, Tao Zhang, Hongtao Gu, Lan Yang, Qingxian Bai and 5 more

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. A short-term prognostic model based on urinary IgG, COAmerican journal of cancer research · 2025
    Article
  3. Article
  4. Article
  5. 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

15 authors.

Shuangshuang JiaDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Lei BiDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Yuping ChuDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Xiao LiuDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Juan FengDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Li XuDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Tao ZhangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Hongtao GuDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Lan YangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Qingxian BaiDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Rong LiangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Biao TianDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Yaya GaoDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Hailong TangDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.
Guangxun GaoDepartment of Hematology, Xijing Hospital, Air Force Medical University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Multiple myeloma (MM) is a highly heterogeneous disease with enormously variable outcomes. It remains to be a major challenge to conduct a more precise estimation of the survival of MM patients. The existing stratifications attached less importance to the prognostic significance of comorbidities. In the present study, we aimed to develop and validate a novel and simple prognostic stratification integrating tumor burden and comorbidities measured by HCT-CI. Method: We retrospectively enrolled 385 consecutive newly diagnosed multiple myeloma (NDMM) patients in Xijing Hospital from January 2013 to December 2020. The cohort between January 2016 and December 2020 was selected as development cohort ( Results: The MM-BHAP model was superior to the ISS stage and partially better than the R-ISS stage according to time-dependent AUC, time-dependent C-index, DCA, IDI, and continuous NRI analyses. In predicting OS, only the MM-BHAP stratification clearly divided patients into three groups while both the ISS stage and R-ISS stage had poor classifications in patients with stage I and stage II. Moreover, the MM-BHAP stratification and the R-ISS stage performed well in predicting PFS, but not for the ISS stage. Besides, the MM-BHAP model was also applied to the patients with age ≤65 or age >65 and with or without HRCA and could enhance R-ISS or ISS classifications. Conclusions: Our study offered a novel simple MM-BHAP stratification containing tumor burden and comorbidities to predict outcomes in the real-world unselected NDMM population.

Indexed as

comorbidityHCT-CImultiple myelomaprognostic modelrisk stratification

Identifiers

PMID35372057
PMCPMC8968003

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.