Evidence map›Paper›PMID 38274836›Full record

ArticleFrontiers in immunology2023

Construction and validation of a prognostic nutritional index-based nomogram for predicting pathological complete response in breast cancer: a two-center study of 1,170 patients.

Fanli Qu, Yaxi Luo, Yang Peng, Haochen Yu, Lu Sun, Shengchun Liu, Xiaohua Zeng

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Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 3 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

28 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Reply to L Zhang et al.Advances in nutrition (Bethesda, Md.) · 2026
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  8. PIV, PNI and HALP score for predicting pathological complete response in breast cancer after neoadjuvant chemotherapy: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  11. Predicting the Effectiveness of 2 Chemotherapy Regimens Applied to Breast Cancer Patients by Nutritional and Inflammatory Status.Medical science monitor : international medical journal of experimental and clinical research · 2026
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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

7 authors.

Fanli QuDepartment of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.
Yaxi LuoDepartment of Rehabilitation, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yang PengDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Haochen YuDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Lu SunDepartment of Thyroid and Breast Surgery, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.
Shengchun LiuDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xiaohua ZengDepartment of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is associated with favorable outcomes in breast cancer patients. Identifying reliable predictors for pCR can assist in selecting patients who will derive the most benefit from NAC. The prognostic nutritional index (PNI) serves as an indicator of nutritional status and systemic immune competence. It has emerged as a prognostic biomarker in several malignancies; however, its predictive value for pCR in breast cancer remains uncertain. The objective of this study is to assess the predictive value of pretreatment PNI for pCR in breast cancer patients. Methods: A total of 1170 patients who received NAC in two centers were retrospectively analyzed. The patients were divided into three cohorts: a training cohort (n=545), an internal validation cohort (n=233), and an external validation cohort (n=392). Univariate and multivariate analyses were performed to assess the predictive value of PNI and other clinicopathological factors. A stepwise logistic regression model for pCR based on the smallest Akaike information criterion was utilized to develop a nomogram. The C-index, calibration plots and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the model. Results: Patients with a high PNI (≥53) had a significantly increased pCR rate (OR 2.217, 95% CI 1.215-4.043, Conclusion: The pretreatment PNI is a reliable predictor for pCR in breast cancer patients. The PNI-based nomogram is a low-cost, noninvasive tool with favorable predictive accuracy for pCR, which can assist in determining individualized treatment strategies for breast cancer patients.

Indexed as

Breast NeoplasmsFemaleHumansNomogramsNutrition AssessmentPrognosisRetrospective Studiesbreast cancerneoadjuvant chemotherapynomogrampathological complete responseprognostic nutritional index

Identifiers

PMID38274836
PMCPMC10808698

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