Evidence map›Paper›PMID 42299331›Full record

ArticleDrug design, development and therapy2026

Toward Optimized Platinum Therapy: A Risk Prediction Model for Toxicity Based on Platinum Accumulation and Its Impact on Treatment Outcomes.

Xiaoting Huang, Chen Chen, Jieting Zheng, Yier Lai, Yi Yang, Yuling Zhang, Ling Fang

Abstract read
In one paragraph

Article in Drug design, development and therapy, 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiaoting Huang *Pharmacy Intravenous Admixture Service, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.ORCID 0009-0008-6141-3243
Chen Chen *Pharmacy Intravenous Admixture Service, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
Jieting ZhengPharmacy Department, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
Yier LaiShantou University Medical College, Shantou, Guangdong, People's Republic of China.
Yi YangShantou University College of Science, Shantou, Guangdong, People's Republic of China.
Yuling ZhangResearch Institute of Clinical Pharmacy, Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
Ling FangPharmacy Department, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Platinum-based chemotherapeutic agents are fundamental in the treatment of various malignancies, yet their long-term efficacy is often compromised by cumulative toxicity. This study investigates the association between platinum accumulation and length of hospital stay (LOS), and develops a predictive tool to optimize individualized platinum therapy. Methods: A total of 300 cancer patients receiving platinum-based chemotherapy were enrolled. Serum platinum concentration was measured on day 21 ± 3 after drug administration. The LOS and adverse events were recorded. Mediation analysis explored underlying mechanisms, and a classification and regression tree (CART) model was constructed for risk prediction. Results: Elevated serum platinum concentration significantly prolonged LOS, primarily mediated through reduced red blood cell count (mediation effect accounted for 32.3%). The CART model identified serum platinum concentration > 534.40 μg/L as a key threshold and major predictor of adverse reactions, alongside age > 60.5 years, serum creatinine > 94.50 μmol/L, and use of cisplatin or carboplatin. The model demonstrated an AUC of 0.782 and accuracy of 75.7%. Conclusion: A serum platinum concentration > 534.40 μg/L serves as a clinically meaningful cutoff for identifying patients at high risk of platinum‑related toxicity. The proposed decision‑tree model offers a clinically actionable framework for the early recognition of these high‑risk individuals, facilitating timely dose management and treatment optimization in clinical practice.

Indexed as

Antineoplastic AgentsCarboplatinCisplatinNeoplasmsAdultAgedFemaleHumansLength of StayMaleMiddle AgedTreatment OutcomeAntineoplastic AgentsCarboplatinCisplatinaccumulationcancerdecision tree modellength of stayplatinumrisk prediction

Identifiers

PMID42299331
PMCPMC13265008

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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.