ArticleCancer informatics2022
Optimizing Drug Response Study Design in Patient-Derived Tumor Xenografts.
Article in Cancer informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- CircRAD23B-208aa Promotes Gastric Cancer Progression by Activating the Unfolded Protein Response through PDIA5 SUMOylation.Research (Washington, D.C.) · 2026Article
- Harnessing a cRGD-Targeted Schottky Junction MXene Nanocomposite for Potent Bladder Cancer Therapy: Dual-Modal PTT/PDT Effects with Immune Activation and Favorable Comparison to Doxorubicin.International journal of nanomedicine · 2026Article
- Oleanolic acid alleviates ovarian cancer by regulating the miR-122/PDK4 axis to induce autophagy and inhibit glycolysisFrontiers in oncology · 2025Article
- Cytidine deaminases APOBEC3C and APOBEC3D promote DNA replication stress resistance in pancreatic cancer cells.Nature cancer · 2024Article
- Inhibition of ubiquitin specific peptidase 8 is effective against 5-fluorouracil resistance in colon cancer via suppressing EGFR and EGFR-mediated signaling pathways.Histology and histopathology · 2024Article
- Radiation Sensitivity: The Rise of Predictive Patient-Derived Cancer Models.Seminars in radiation oncology · 2023Review
- Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction.Frontiers in immunology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patient-derived tumor xenograft (PDX) models were used to evaluate the effectiveness of preclinical anticancer agents. A design using 1 mouse per patient per drug (1 × 1 × 1) was considered practical for large-scale drug efficacy studies. We evaluated modifiable parameters that could increase the statistical power of this design based on our consolidated PDX experiments. Real studies were used as a reference to investigate the relationship between statistical power with treatment effect size, inter-mouse variation, and tumor measurement frequencies. Our results showed that large effect sizes could be detected at a significance level of .2 or .05 under a 1 × 1 × 1 design. We found that the minimum number of mice required to achieve 80% power at an alpha level of .05 under all situations explored was 21 mice per group for a small effect size and 5 mice per group for a medium effect size.
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What OpenQuestion holds
Registered trials
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.