ArticlePloS one2016
Independent Pre-Transplant Recipient Cancer Risk Factors after Kidney Transplantation and the Utility of G-Chart Analysis for Clinical Process Control.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Cancer Risks in Solid Organ Transplant Recipients: Results from a Comprehensive Analysis of 72 Cohort Studies.Oncoimmunology · 2020Pooled it
- Clinical management of cancer after kidney transplantation.Frontiers in immunology · 2026Review
- Endocrine malignancies: a still neglected issue in kidney transplantation.Frontiers in medicine · 2025Review
- Post-Kidney Transplant Cancer: A Real-World Retrospective Analysis From a Single Italian Center.Transplant international : official journal of the European Society for Organ Transplantation · 2024Article
- Effects of solid organ transplantation on the risk of developing thyroid cancer: a systematic review and meta-analysis.Gland surgery · 2022Article
- Novel non-cystic features of polycystic kidney disease: having new eyes or seeking new landscapes.Clinical kidney journal · 2021Review
- Monitoring of high-yield and periodical processes in health care.Health care management science · 2020Article
- Thanatometabolomics: introducing NMR-based metabolomics to identify metabolic biomarkers of the time of death.Metabolomics : Official journal of the Metabolomic Society · 2019Article
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. PATIENTS AND
methods1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences.
resultsCancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33-3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05).
conclusionsRisk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm signals to trigger Kaizen events and audits for root-cause analysis of relevant detection rate changes. Further, comparative G-chart analysis would enable benchmarking of cancer surveillance processes between centers.
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