Medizinische Universität Graz - Research portal

Logo MUG Resarch Portal

Selected Publication:

SHR Neuro Cancer Cardio Lipid Metab Microb

Zigeuner, R; Pummer, K.
Predicting cancer-control outcomes in patients after nephron sparing surgery.
Arch Ital Urol Androl. 2009; 81(2): 91-95.
PubMed

 

Leading authors Med Uni Graz
Pummer Karl
Zigeuner Richard
Altmetrics:

Dimensions Citations:

Plum Analytics:
Abstract:
This article focuses on prognostic factors after nephron-sparing surgery (NSS) for renal cell carcinoma (RCC). A variety of prognostic models has been developed to predict patients' outcome after surgery for RCC. The populations which these models have been based on, however, mainly consisted of patients undergoing radical nephrectomy, whereas NSS represented only a minority. On the other hand, NSS is increasingly gaining acceptance for unilateral small renal masses and a normal contralateral kidney (elective NSS). Meanwhile many large series reporting favourable outcomes after elective NSS have been published. Purely elective NSS series constantly fail to demonstrate prognostic factors due to the rarity of cancer relapse. In other series including larger proportions of imperative NSS cancer recurrence has been reported more frequently, thus prognostic capabilities of established prognostic factors for RCC like TNM-stage, tumour grade, tumour size, symptoms, histological subtypes, or necrosis could be shown. One additional prognostic parameter specific for NSS not applicable in a nephrectomy setting is imperative indication for NSS, which is associated with poorer prognosis than elective NSS. In contrast, positive surgical margins after NSS uniformly revealed no unfavourable impact. Laparoscopic NSS is increasingly performed at selected centres. Long-term outcome data are still very limited, longer follow-up is needed to conclude whether the laparoscopic approach by itself impacts on prognosis. At present, it is still unclear whether the published prognostic models are reliably applicable for the NSS population. Thus, validation of these models in large multi-institutional databases is encouraged.
Find related publications in this database (using NLM MeSH Indexing)
Carcinoma, Renal Cell - pathology
Humans -
Kidney Neoplasms - pathology
Laparoscopy - methods
Multivariate Analysis -
Neoplasm Staging -
Nephrectomy - methods
Nephrons -
Nomograms -
Outcome Assessment (Health Care) -
Patient Selection -
Predictive Value of Tests -
Prognosis -
Recurrence -
Time Factors -
Treatment Outcome -
Urologic Surgical Procedures - methods

© Med Uni GrazImprint