Evidence map›Paper›PMID 37177980›Full record

ArticleThe oncologist2023

Long-Term Risk of Subsequent Malignant Neoplasms Among Childhood and Adolescent Lymphoma Survivors (1975-2013): A Population-Based Predictive Nomogram.

Junqi Liu, Qingzhu Zheng, Narasimha M Beeraka, Xiao Zhang, Tingxuan Li, Ruixia Song, Di Zhao, Ruitai Fan

Open access · goldAbstract read
In one paragraph

Article in The oncologist, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

3 citing papers in PubMed, 3 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

8 authors at 2 institutions in 2 countries.

Junqi LiuDepartment of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Erqi, Zhengzhou, People's Republic of China.
Qingzhu ZhengDepartment of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Erqi, Zhengzhou, People's Republic of China.
Narasimha M BeerakaRaghavendra Institute of Pharmaceutical Education and Research (RIPER), Anantapuramu, Chiyyedu, Andhra Pradesh, India.
Xiao ZhangDepartment of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Erqi, Zhengzhou, People's Republic of China.
Tingxuan LiDepartment of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Erqi, Zhengzhou, People's Republic of China.
Ruixia SongDepartment of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Erqi, Zhengzhou, People's Republic of China.
Di ZhaoEndocrinology Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People's Republic of China.
Ruitai FanDepartment of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Erqi, Zhengzhou, People's Republic of China.
First Affiliated Hospital of Zhengzhou University · CNSechenov University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStudies are needed to assess risk factors pertinent to the incidence of secondary malignancies among childhood and adolescent lymphoma survivors. We aimed to identify risk factors pertinent to the incidence of secondary malignancies and subsequently establish a clinically practical predictive nomogram.

methodsA total of 5561 patients who were diagnosed with primary lymphoma below the age of 20 years between 1975 and 2013 and survived for at least 5 years were identified. Standardized incidence ratio (SIR) and excess risk (ER) analysis were performed by sex, age, and year when primary lymphoma was diagnosed, sites and types of primary lymphoma, and therapy strategies. Univariable and multivariable logistic regression were used to identify independent risk factors for adolescent and childhood lymphoma-related secondary malignancies. Based on 5 factors (age, time from lymphoma diagnosis, gender, lymphoma type, and therapy), a nomogram for predicting the risk of a secondary malignancy for patients with childhood and adolescent primary lymphoma was established.

resultsAmong 5561 lymphoma survivors, 424 developed a secondary malignancy. Females (SIR = 5.34, 95% CI, 4.73-5.99; ER = 50.58) exhibited a higher SIR and ER than males (SIR = 3.28, 95% CI, 2.76-3.87; ER = 15.53). Blacks were at a higher risk than Caucasians or others. Nodular lymphocyte-predominant Hodgkin lymphoma survivors exhibited typically high SIR (13.13, 95% CI, 6-24.92) and ER (54.79) among all lymphoma classifications. Lymphoma survivors who underwent radiotherapy, whether they received chemotherapy or not, had typically higher SIR and ER. Among all types of secondary malignancies, "bone and joint neoplasms" (SIR = 11.07, 95% CI, 5.52-19.81) and "soft tissue neoplasms" (SIR = 12.27, 95% CI, 7.59-18.76) presented significantly high SIR whereas "breast cancer" and "endocrine cancer" associated with higher ER. The median diagnosis age of secondary malignancies was 36 years old, and the median time interval between the diagnosis of two malignancies was 23 years. A nomogram was constructed to predict the risk of secondary malignancies in patients diagnosed with primary lymphoma before 20 years of age. After internal validation, the AUC and C-index of the nomogram are 0.804 and 0.804, respectively. CONCLUSION AND RELEVANCE: The established nomogram provides a convenient and reliable tool for predicting the risk of a secondary malignancy among childhood and adolescent lymphoma survivors, concluding significant concern for lymphoma survivors with high-risk estimates.

Indexed as

Breast NeoplasmsLymphomaNeoplasmsNeoplasms, Second PrimaryAdolescentAdultChildFemaleHumansIncidenceMaleNomogramsRisk FactorsSurvivorsYoung Adultadolescent lymphomachildhood lymphomanomogramsecondary malignancies

Identifiers

PMID37177980
PMCPMC10485277
OpenAlexW4376503927

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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.