Evidence map›Paper›PMID 41843055›Full record

ArticleInternational journal of clinical oncology2026

Development and validation of a predictive model for pleural effusion control following talc pleurodesis in malignant pleural effusion.

Shunya Hanawa, Masaru Ejima, Mari Sugawara, Natsushi Kubota, Rina Kato, Kotaro Hanawa, Seishi Higashi, Satoko Hanada, Reiko Taki

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Article in International journal of clinical oncology, 2026. 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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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

9 authors.

Shunya HanawaDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan. s.hanawa.1443@gmail.com.
Masaru EjimaDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan. m.ejima245@gmail.com.ORCID http://orcid.org/0000-0001-9842-778X
Mari SugawaraDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.
Natsushi KubotaDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.
Rina KatoDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.
Kotaro HanawaDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.
Seishi HigashiDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.
Satoko HanadaDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.
Reiko TakiDepartment of Respiratory Medicine, Musashino Red Cross Hospital, 1-26-1 Kyonan-Cho, Musashino-Shi, Tokyo, 180-8610, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTalc slurry pleurodesis is widely used for malignant pleural effusion (MPE); however, its success rate ranges from 50 to 75%, and reliable predictors are lacking. This study aimed to identify predictors of pleural effusion control failure following pleurodesis and develop a short-term predictive scoring system.

methodsWe retrospectively analyzed 170 patients with MPE who underwent talc pleurodesis at a single center between 2014 and 2024. The cohort was divided into training (n = 136) and validation (n = 34) cohorts. Logistic regression was used to identify independent predictors of pleural effusion control failure within 30-90 days.

resultsThe most common primary tumors were lung, breast, and ovarian cancers. Pleural effusion was controlled in 70.6% of cases. Univariate analysis identified low body mass index, supportive care alone, Grade 2 collapse of the lower lung field post-drainage, extensive pulmonary consolidation, large tumor (≥ 7 cm), hypoalbuminemia, and positive pleural fluid cytology (Class III or higher) to be associated with pleural effusion control failure. Multivariate analysis revealed that massive pleural effusion (P = 0.048), supportive care alone (P < 0.001), and Grade 2 lung collapse (P = 0.003) were independent predictors of pleural effusion control failure. A scoring system incorporating these factors was validated in a validation cohort, demonstrating a control rate of approximately 90%, 60% and 30% in patients scoring ≤ 1, 2 and ≥ 3 points, respectively.

conclusionsThe scoring system may support early decision-making regarding talc pleurodesis and palliative strategies, potentially improving quality of life in patients with MPE.

Indexed as

Pleural Effusion, MalignantPleurodesisTalcAgedAged, 80 and overFemaleHumansMaleMiddle AgedRetrospective StudiesTalcMalignant pleural effusionPredictive modelTalc pleurodesis

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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.