Evidence map›Paper›PMID 40622486›Full record

ArticleDiscover oncology2025

Demographic and clinical predictors of treatment outcomes in invasive lobular carcinoma breast cancer: insights from Cox regression analysis.

Sonia Kaindal, B Venkataramana

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Sonia KaindalDepartment of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India.
B VenkataramanaDepartment of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India. venkataramana.b@vit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive lobular carcinoma (ILC) ranks as the second most prevalent type of breast cancer after invasive ductal carcinoma (IDC). Understanding the demographics, clinical, and treatment outcomes of patients with ILC is essential for developing personalized treatment strategies. The purpose of this study is to evaluate the risk factors, treatment efficacy, demographics, and effects of marital status on treatment approaches for patients with lobular carcinoma. The data retrieved from the SEER program included 2,085 patients with lobular carcinoma. Descriptive statistics describe their clinical and demographical characteristics, while inferential statistics, including the Pearson chi-square test and Cox regression models, assess treatment outcomes based on age and clinicopathological factors. Among the cohort, 7.9% of patients were aged 30-44, 40.1% were aged 45-59, and 52% were aged 60-74. The analysis indicated that patients aged 45-59 predominantly received radiation therapy, while those aged 60-74 primarily underwent chemotherapy. Compared to older individuals, younger patients demonstrated a more favorable response to chemotherapy (HR = 0.653, 95% CI: 0.261-1.633) and radiation therapy (HR = 0.625, 95% CI: 0.249-1.565). Age at diagnosis was an independent factor in breast cancer of lobular carcinoma. The Cox regression models revealed significant disparities in treatment effects across different age groups and clinicopathological characteristics. The chi-square analysis showed no significant associations for most variables, indicating that unmeasured factors influence chemotherapy and radiation therapy. A frailty model better captures risk factors, improving treatment decision-making and patient outcome analysis. This study emphasizes the need to evaluate demographic and clinical factors in treatment planning for lobular carcinoma patients. The findings suggest that personalized treatment strategies should be developed to address the varying responses to treatment among different patient cohorts.

Indexed as

Cox regressionLog rank testSEER databaseSurvival probability

Identifiers

PMID40622486
PMCPMC12234933

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LicenceCC BY
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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.