Observational studyEuropean radiology2015
Optimal follow-up intervals in active surveillance of renal masses in patients with von Hippel-Lindau disease.
Observational study in European radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- The kidney imaging surveillance scoring system (KISSS): using qualitative MRI features to predict growth rate of renal tumors in patients with von-Hippel Lindau (VHL) syndrome.Abdominal radiology (New York) · 2024Article
- Evaluation, diagnosis and surveillance of renal masses in the setting of VHL disease.World journal of urology · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo estimate an optimal follow-up (FU) interval for von Hippel-Lindau (VHL) patients with renal masses (RMs) by determining tumour growth rates from growth curves.
methodsThirty lesions (47.6%) were classified as solid tumours (STs) and 33 (52.4%) as complex cysts (CCs). Variations in lesion volume over time were analyzed. For 53 lesions, we calculated the growth rate during the period when the volume of the lesion changed most rapidly, and called this the fast growth rate (FGR).
resultsThe STs initially grew fast, followed by a period of slower growth. The CCs varied in volume over time, associated with variable amounts of their fluid component. The FGR correlated better with the latest volume for STs (r = 0.905) than for CCs (r = 0.780). An optimal FU interval between 3 and 12 months was derived by combining the FGR calculated from the curve with the latest volume measured.
conclusionsAnalyzing growth curves and related kinetic parameters for RMs in VHL patients could be useful with a view to optimizing the subsequent FU interval and improving the active surveillance program. KEY POINTS: • Measuring volume changes over time enables tumour growth curves to be charted. • Renal solid tumours increase in volume with a typical sigmoidal curve. • Complex cysts may increase and decrease in volume spontaneously over time. • The fast growth rate of solid tumours correlates with their latest volume. • The fast growth rate can orient the scheduling of subsequent follow-ups.
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Registered trials
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