Disease progression and survival


As with any intervention, the goal is to maximize disease cure while minimizing harm from treatment. For bladder cancer, this maxim seems especially relevant. 

Adding greater complexity to the treatment decision-making analysis is the reality that many patients after appropriate treatment (chemotherapy and surgery)14 for invasive bladder cancer will experience a disease recurrence and ultimately will die of bladder cancer. Although variable and, as expected, related to final pathologic staging, single institutional and multi-institutional studies have reported rates of recurrent bladder cancer after surgery ranging from 21.6%-50%.15-17 Additionally, overall survival during follow-up for these patients similarly ranges from 36%-50%.


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For example, Shariat et al reported the experience of three high-volume radical cystectomy centers and demonstrated varying survivals stratified by pathologic stage. In this large cohort of 888 patients, the overall five-year progression-free survival (PFS) and bladder-cancer specific (BCS) survival rates were 58.3% and 65.7%, respectively.18 

However, PFS and BCS survival rates were 88.8%, 75.3%, 80.8%, 71.6%, 44.2%, and 28.4% and 93.9%, 87.2%, 85.9%, 78.9%, 47.7%, and 31.0% for pTa, pTis, pT1, pT2, pT3, and pT4 bladder cancer, respectively.18 Similarly, patients with lymph node positive disease at the time of radical cystectomy had three-year PFS and BCS of 29.1% and 37.5%.

Thus, although radical cystectomy is an effective treatment for bladder cancer, it is associated with significant perioperative risk, and its efficacy in producing a long-term cure in certain subsets of patients (those with greater than pT3 disease and positive lymph nodes) is less than 50%, creating a therapeutic “Catch-22” for the urologic oncologist.


Recent competing risks models for renal cell carcinoma (RCC) have elegantly quantified the risk of death from kidney cancer versus the risk of death from a patient’s associated medical problems.19,20 For these risk assessments, the time frame associated with these calculations is five years.

Unlike RCC, where a large group of patients can defer treatment for up to five years or perhaps even longer,21 bladder cancer patients do not have this luxury. In fact, if left untreated, patients with muscle-invasive bladder cancer (MIBC) will die of their disease within 18-24 months.3

It is a rare patient with MIBC who will present with medical comorbidities so severe that their risk of death not due to bladder cancer outweighs their risk of death due to bladder cancer, making a competing-risks analysis somewhat inapplicable in this clinical scenario.

Therefore, given all the decision-making intricacies associated with radical surgery for invasive bladder cancer, there is a real need for improved risk assessment tools to objectify a patient’s perioperative risk for adverse outcomes after surgery versus their disease risk and likelihood of cure with invasive/maximal therapy.


Few objective criteria for making treatment decisions


Unfortunately, the ability to accurately predict a patient’s pathologic stage with bladder cancer is poor,22 thus leaving much of the modifiable risk assessment to preoperative evaluation of a patient’s physiologic state. In general, however, available preoperative risk assessment tools to objectively predict a patient’s surgical risk are either lacking or too time-consuming.

As such, surgical decision-making is overly subjective and full of physician and patient biases that unduly guide treatment decisions. Due to this lack of objective data, many important treatment decisions are made on incomplete data or instinct. In fact, it has been shown by behavioral economists that people will make decisions based on the perception of potential gain or loss. Interestingly, people tend to make decisions that are more risk-taking when they are presented with a scenario that is framed as a loss.23

Despite these flaws, the physician is faced with a population that is living longer, and once patients reach a certain age, their likelihood of still having a significant life expectancy is high. Thus, the decision to operate/treat must account for a patient’s life span versus the natural history and severity of a given disease.

Furthermore, the treatment decision-making process must somehow be able to adequately quantitate a patient’s ability to survive and recover from a given surgery with an acceptable rate of morbidity and/or mortality. Finding or developing tools to fill this void are clearly needed.


This clinical challenge is no more apparent than in the elderly bladder cancer patient. To date, one of the only pieces of objective data that reliably correlate with adverse perioperative outcomes is increasing patient age. As already mentioned, in patients with invasive bladder cancer who require radical cystectomy, population-based and institutional datasets show a clear increasing risk of 90-day postoperative mortality with increasing age.12,13

Furthermore, this relationship is similarly also present in the elderly undergoing pancreatic and esophageal surgeries (15%-20%).24 Although these surgeries carry a significantly increased risk of perioperative death when compared with other surgeries, it is worth highlighting that this percentage is still a minority. Unfortunately, what is lacking is the ability to definitively and objectively identify the vast majority of patients who will recover well from this surgery while sparing the remaining subset of patients from an adverse outcome.


It is important to note that this relationship between perioperative outcomes and age exists in other surgical populations that are not undergoing as extensive a surgical procedure. Polanczyk et al examined the relationship among age, length of stay, and complications in patients undergoing non-cardiac surgery. In this large study, the authors found a statistically significant relationship between increasing age and major or fatal perioperative complications.25

Patients aged 80 years or older were 3.5 times more likely to die during their hospitalization compared with patients younger than 80 years.25 Similarly, Hamel et al. assessed the relationship between surgical risk and age. The findings of this analysis were very similar to that of Polanczyk et al, demonstrating a significantly higher rate of complications (p < 0.001) and mortality (p < 0.001) for patients older than 80 years as compared to patients younger than 80 years.26 Specifically, for every year above the age of 80, a patient had a 5% increase in post-operative mortality.26