Evidence map›Paper›PMID 32898941›Full record

ArticleCancer research and treatment2021

Prediction of Pathologic Response to Neoadjuvant Chemoradiotherapy in Patients with Esophageal Squamous Cell Carcinoma Incorporating Hematological Biomarkers.

Yingjia Wu, Jinbin Chen, Lei Zhao, Qiaoqiao Li, Jinhan Zhu, Hong Yang, Suping Guo, Mian Xi

Open access · diamondAbstract read
In one paragraph

Article in Cancer research and treatment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 7% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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  14. A machine learning approach usingFrontiers in immunology · 2024
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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 3 institutions in 1 country.

Yingjia WuState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Jinbin ChenState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Lei ZhaoState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Qiaoqiao LiState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Jinhan ZhuState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Hong YangState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Suping GuoState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Mian XiState Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China.
Sun Yat-sen University Cancer Center · CNState Key Laboratory of Oncology in South ChinaSun Yat-sen University · CN

Funding

Central Universities in China 19ykpy176Medical Scientific Research Foundation of Guangdong Province C2015030Natural Science Foundation of Guangdong Province 2019A1515011420
6 · The paper itself

Abstract

purposeThis study aimed to develop a nomogram for predicting pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (CRT) in patients with esophageal squamous cell carcinoma (ESCC) by integrating hematological biomarkers and clinicopathological characteristics. MATERIALS AND

methodsBetween 2003 and 2017, 306 ESCC patients who underwent neoadjuvant CRT followed by esophagectomy were analyzed. Besides clinicopathological factors, hematological parameters before, during, and after CRT were collected. Univariate and multivariate logistic regression analyses were performed to identify predictive factors for pCR. A nomogram model was built and internally validated.

resultsAbsolute lymphocyte count (ALC), lymphocyte to monocyte ratio, albumin, hemoglobin, white blood cell, neutrophil, and platelet count generally declined, whereas neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) increased significantly following neoadjuvant CRT. After surgery, 124 patients (40.5%) achieved a pCR. The pCR group demonstrated significantly more favorable survival than the non-pCR group. On multivariate analysis, significant factors associated with pCR included sex, chemotherapy regimen, post-CRT endoscopic finding, pre-CRT NLR, ALC nadir during CRT, and post-CRT PLR, which were incorporated into the prediction model. The nomogram indicated good accuracy in predicting pCR, with a C-index of 0.75 (95% confidence interval, 0.71 to 0.78).

conclusionFemale, chemotherapy regimen of cisplatin/vinorelbine, negative post-CRT endoscopic finding, pre-CRT NLR (≤ 2.1), ALC nadir during CRT (> 0.35 ×109/L), and post-CRT PLR (≤ 83.0) were significantly associated with pCR in ESCC patients treated with neoadjuvant CRT. A nomogram incorporating hematological biomarkers to predict pCR was developed and internally validated, showing good predictive performance.

Indexed as

AdultAgedBiomarkers, TumorChemoradiotherapyEsophageal Squamous Cell CarcinomaFemaleHumansMaleMiddle AgedNeoadjuvant TherapyBiomarkers, TumorEsophageal squamous cell carcinomaHematological biomarkerNeoadjuvant chemoradiotherapyPathologic responsePrediction model

Identifiers

PMID32898941
PMCPMC7812014
OpenAlexW3083642835

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.