Evidence map›Paper›PMID 35996151›Full record

ArticleBMC medicine2022

Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics.

Jiawei Lv, Chenfei Wu, Junyan Li, Foping Chen, Shiwei He, Qingmei He, Guanqun Zhou, Jun Ma, Ying Sun, Denghui Wei and 1 more

Abstract read
In one paragraph

Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Jiawei Lv *Department of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China. lvjw@sysucc.org.cn.
Chenfei Wu *Department of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China.
Junyan Li *State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Foping Chen *Department of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China.
Shiwei He *State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Qingmei HeState Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Guanqun ZhouDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China.
Jun MaDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China.
Ying SunDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China. sunying@sysucc.org.cn.
Denghui WeiState Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. weidh@sysucc.org.cn.
Li LinDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Center for Precision Medicine of Sun Yat-sen University, Guangzhou, 510060, People's Republic of China. linli@sysucc.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSignificant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions that they do not fully capture patient clinical benefits. Currently, there is a paucity of data regarding the clinical implication of biological responses assessed by liquid biopsy of on-treatment circulating tumor DNA (ctDNA). Here, we investigated whether biological response evaluated by ctDNA kinetics added critical information to the RECIST, and whether integrating on-treatment biological response information refined risk stratification of cancer patients.

methodsIn this population-based cohort study, we included 821 patients with Epstein-Barr virus (EBV)-associated nasopharynx of head and neck cancer (NPC) receiving sequential neoadjuvant chemotherapy (NAC) and chemoradiotherapy (CRT), who had pretreatment and on-treatment cfEBV DNA and magnetic resonance imaging (MRI) surveillance. Biological responses evaluated by cfEBV DNA were profiled and compared with conventional MRI-based RECIST evaluation. The inverse probability weighting (IPW)-adjusted survival analysis was performed for major survival endpoints. The Cox proportional hazard regression [CpH]-based model was developed to predict the on-treatment ctDNA-based individualized survival.

resultsOf 821 patients, 71.4% achieved complete biological response (cBR) upon NAC completion. RECIST-based response evaluations had 25.3% discordance with ctDNA-based evaluations. IPW-adjusted survival analysis revealed that cfEBV DNA

conclusionsOur study helps advance the implementation of ctDNA-based testing in therapeutic response evaluation for a refined risk stratification. The dynamic and refined risk profiling would tailor future liquid biopsy-based risk-adapted personalized therapy.

Indexed as

Circulating Tumor DNAEpstein-Barr Virus InfectionsNasopharyngeal NeoplasmsCohort StudiesHerpesvirus 4, HumanHumansNeoplasm Recurrence, LocalPrognosisRisk AssessmentCirculating Tumor DNACirculating tumor DNALiquid biopsyNasopharyngeal carcinomaRECISTRisk-adapted personalized therapy

Identifiers

PMID35996151
PMCPMC9396864

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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.