Michael Organ1, Michael Jewett2, Joan Basiuk1, Christopher Morash3, Stephen Pautler4, D Robert Siemens5, Simon Tanguay6, Martin Gleave7, Darrell Drachenberg8, Raymond Chow9, Joseph Chin4, Andrew Evans10, Neil Fleshner2, Brenda Gallie11, Masoom Haider12, John Kachura12, Antonio Finelli2, Ricardo A Rendon1. 1. Faculty of Medicine, Department of Urology, Dalhousie University, Halifax, NS; 2. Department of Surgery, Division of Urology, University of Toronto, Toronto, ON; Kidney Cancer Research Network of Canada, Toronto, ON; 3. Department of Surgery, Division of Urology, University of Ottawa, Ottawa, ON; 4. Division of Urology, Schulich School of Medicine and Dentistry, Western University, London, ON; 5. Department of Urology, Queen's University, Kingston, ON; 6. Division of Urology, McGill University, Montreal, QC; 7. Department of Urologic Sciences, University of British Columbia, Vancouver, BC; 8. Faculty of Medicine, Division of Urology, University of Manitoba, Winnipeg, MB; 9. Department of Health Informatics, Princess Margaret Hospital, Toronto, ON; 10. Department of Pathology and Laboratory, Faculty of Medicine, University of Toronto, Toronto, ON; 11. Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON; 12. Department of Medical Imaging, University of Toronto, Toronto, ON.
Abstract
INTRODUCTION: Most small renal masses (SRMs) are diagnosed incidentally and have a low malignant potential. As more elderly patients and infirm patients are diagnosed with SRMs, there is an increased interest in active surveillance (AS) with delayed intervention. Patient and tumour characteristics relating to aggressive disease have not been well-studied. The objective was to determine predictors of growth of SRMs treated with AS. METHODS: A multicentre prospective phase 2 clinical trial was conducted on 207 SRMs in 169 patients in 8 institutions in Canada from 2004 to 2009; in these patients treatment was delayed until disease progression. Patient and tumour characteristics were evaluated to determine predictors of growth of SRMs by measuring rates of change in growth (on imaging) over time. All patients underwent AS for presumed renal cell carcinoma (RCC) based on diagnostic imaging. We used the following factors to develop a predictive model of tumour growth with binary recursive partitioning analysis: patient characteristics (age, symptoms at diagnosis) and tumour characteristics (consistency [solid vs. cystic] and maximum diameter at diagnosis. RESULTS: With a median follow-up of 603 days, 169 patients (with 207 SRMs) were followed prospectively. Age, symptoms at diagnosis, tumour consistency and maximum diameter of the renal mass were not predictors of growth. This cohort was limited by lack of availability of patient and tumour characteristics, such as sex, degree of endophytic component and tumour location. CONCLUSION: Slow growth rates and the low malignant potential of SRMs have led to AS as a treatment option in the elderly and infirm population. In a large prospective cohort, we have shown that age, symptoms, tumour consistency and maximum diameter of the mass at diagnosis are not predictors of growth of T1a lesions. More knowledge on predictors of growth of SRMs is needed.
INTRODUCTION: Most small renal masses (SRMs) are diagnosed incidentally and have a low malignant potential. As more elderly patients and infirm patients are diagnosed with SRMs, there is an increased interest in active surveillance (AS) with delayed intervention. Patient and tumour characteristics relating to aggressive disease have not been well-studied. The objective was to determine predictors of growth of SRMs treated with AS. METHODS: A multicentre prospective phase 2 clinical trial was conducted on 207 SRMs in 169 patients in 8 institutions in Canada from 2004 to 2009; in these patients treatment was delayed until disease progression. Patient and tumour characteristics were evaluated to determine predictors of growth of SRMs by measuring rates of change in growth (on imaging) over time. All patients underwent AS for presumed renal cell carcinoma (RCC) based on diagnostic imaging. We used the following factors to develop a predictive model of tumour growth with binary recursive partitioning analysis: patient characteristics (age, symptoms at diagnosis) and tumour characteristics (consistency [solid vs. cystic] and maximum diameter at diagnosis. RESULTS: With a median follow-up of 603 days, 169 patients (with 207 SRMs) were followed prospectively. Age, symptoms at diagnosis, tumour consistency and maximum diameter of the renal mass were not predictors of growth. This cohort was limited by lack of availability of patient and tumour characteristics, such as sex, degree of endophytic component and tumour location. CONCLUSION: Slow growth rates and the low malignant potential of SRMs have led to AS as a treatment option in the elderly and infirm population. In a large prospective cohort, we have shown that age, symptoms, tumour consistency and maximum diameter of the mass at diagnosis are not predictors of growth of T1a lesions. More knowledge on predictors of growth of SRMs is needed.
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