Not all prognostic (predictive) models for kidney cancer recurrence or overall survival use the same clinical criteria.  The information below builds on the study "Post nephrectomy management of localized renal cell carcinoma. From risk stratification to therapeutic evidence in an evolving clinical scenario.", April 2023, by Dr. Chiara Ciccarese (researcher at Università Cattolica del Sacro Cuore and Oncologist at Fondazione Policlinico Gemelli IRCCS. Rome, Italy) and colleagues.  Using this work, I build upon the model as well as entered my clinical case through each model for comparison of predicted outcomes.

The models included in the analysis are designed for post-nephrectomy (partial or radical) for renal cell carcinoma (RCC) of the three most common subtypes - clear cell, papillary, and chromophobe.  

As pointed out in the literature, physicians / scientists in the medical field have developed prognostic models to improve the ability to predict accurately the outcome for patients who are treated surgically for RCC since 2001 (or earlier).  Prognostic algorithms can be used to counsel patients, determine the need for adjuvant therapy, stratify patients for clinical trials, and develop appropriate postoperative surveillance programs that are tailored to a patient's risk for disease progression. [1]

It needs to be stressed that calculations from any prognostic model is an average based on studies conducted to-date, are usually based on data that is at least five years old and does not take into account advances in treatment or changes in general, an individual's overall health, lifestyle, environmental factors, etc.  When using a prognostic nomogram, the calculations for your predicted cancer recurrence or overall survival are not specific to you.  They are averages based on similar patients that have been included in a database.  That being said, many kidney cancer patients like me, want a more informed prediction of RCC recurrence and overall life expectancy rather than none at all.  Physicians / medical centers that utilize data from prognostic models that have been validated by research studies in addition to the physicians' ongoing experience in treating patients and their outcomes, helps to inform regarding the ongoing accuracy of the existing prognostic models in the treatment recommendations for a patient's unique clinical presentation. 

The models will continue to advance as the science in the medical field does - with the discovery of new biomarkers, molecular features, gene and expression profiling, etc.[2]