Competing risks analysis

Kidney cancer. Principles and practice. Second edition. Primo N. Lara, Jr. Eric Jonasch (Editors). Springer International Publishing (2015)

All choices are made in the context of a riskbenefit balance, and healthcare decisions are no exception (Fig. 9.1). The decision to proceed to treatment in young, healthy patients with localized RCC is relatively straightforward, since even small oncologic risks are not acceptable in the face of a long life expectancy. Elderly and/or comorbid patients require a judicious clinical strategy, since in this population, medical comorbidities and non-renal malignancies that are yet to be diagnosed compete with kidney cancer as the primary cause of death. Furthermore, the potential negative impact on the patient’s quality of life due to unintended medical/surgical complications must be accounted for in the treatment decision-making process.

The risk-benefit equation must be seriously considered when one realizes that the proportion of the US population who will be aged 65 years or older in 2030 is estimated to be 20% [15]. Some authors have estimated that 60% of cancers and 80% of all cancer-related deaths in the United States occur in patients over the age of 65 [16]. Similarly, as patients age, they develop medical comorbidities that may be severe enough to impact their ability to receive or tolerate optimal cancer therapies [17]. Thus, the severity of a patient’s comorbidity needs to be contextualized against the biologic behavior of the cancer.

Today, such decision making regarding risks and trade-offs in the management of localized RCC remain largely qualitative; however, clinically useful methods to quantitate risk are beginning to emerge. For instance, several comorbidity indices and scores have been proposed [18], and new approaches are steadily being introduced [19]. The Charlson Comorbidity Index (CCI) [20] is one of the best studied and most commonly employed methods for risk stratification [18]. The CCI incorporates 19 disease entities that include such ailments as cardiovascular, pulmonary, hepatic, and renal dysfunction. The degree to which each condition contributes to the index depends on that condition’s calculated impact on mortality. Today, even in a busy clinical setting, the CCI can be rapidly calculated using web-based tools (e.g., http://www.medal. org/visitor/www/qhc/index.html).

Another potentially useful objective measure of a patient’s risk with surgery is the preoperative measurement of a patient’s “frailty.” Originally developed by geriatricians, frailty is a relatively new concept that encompasses not only a patient’s chronologic age but also a patient’s ability to withstand physiologic stressors. Fried et al. initially introduced this concept and described frailty “as a biologic syndrome of decreased reserve and resistance to stressors, resulting from cumulative declines across multiple physiologic systems, and causing vulnerability to adverse outcomes” [21]. In their initial study, Fried and colleagues operationalized the measurement of frailty focusing on the following domains: shrinking (weight loss or sarcopenia), weakness, slowness, poor endurance/exhaustion, and low activity. More recent studies have shown that the preoperative identification of intermediately frail or frail patients can predict for postoperative adverse events [22]. Ideally, in the future, an objective frailty score could be combined with other measures to develop a refined scale to precisely predict a patient’s risk of adverse events with surgical intervention.

__Kidney Cancer_ Principles and Practice-Springer International Publishing (2015) 9.1

Fig. 9.1. Risk assessment algorithm for a patient with newly diagnosed localized renal cell carcinoma. Assessing risk occurs throughout the continuum of patient care. Risk assessment during initial evaluation requires quantitating treatment trade-offs in an objective manner. Pretreatment risk management requires education and communication about specific risks associated with a chosen therapy. Treatment risk management includes abatement of those risks during therapy using objective, metric-based data. Finally, posttreatment risk management involves mitigating future progression, complications, and anxiety using objective, data-driven strategies

Also, in order to make informed and calculated decisions regarding the management of small localized renal masses, the physician must be able to estimate a patient’s probability of dying from localized RCC and compare this to the patient’s chances of dying from competing causes. Indeed, such predictive models have been developed for non-genitourinary solid malignancies [23, 24]. Similar tools are starting to emerge for localized RCC [25–27]. Our group recently developed a nomogram from a multivariable model based on over 30,000 patients from the Surveillance, Epidemiology, and End Results (SEER) program database who had resection of localized RCC [27]. The nomogram affords the clinician and the patient an opportunity to quantitate three competing 5-year mortality outcomes: (1) death from RCC, (2) death from other (nonRCC) cancers, and (3) non-cancer death. For instance, using the nomogram, a 75-year-old white male with a 4 cm tumor would have a 5-year mortality of 5% from RCC versus 4.5% from other cancers and 14% from noncancerous causes. Even more recently, this nomogram has been adjusted to include a patient’s comorbidities, using the CCI [28]. In light of these competing risks and the known short-term indolent behavior of many localized RCC, active surveillance (AS) has emerged as a viable treatment strategy for patients with renal tumors. In this situation, RMB may prove beneficial in objectively evaluating the histology and Fuhrman grade in an attempt to more accurately predict the behavior of the mass.

__Kidney Cancer_ Principles and Practice-Springer International Publishing (2015) 9.2

Fig. 9.2. RENAL nephrometry scoring system

When considering AS as a management strategy for a newly diagnosed renal mass, it is helpful to consider absolute, relative, and elective indications. Absolute indications include patients in whom surgery poses an immediate and unacceptable risk of mortality. Relative indications for observation include concomitant diseases, such as a second malignancy and/or significant but not overriding medical comorbidities. Lastly, some patients may simply wish to undergo a period of AS despite being low-risk surgical candidates. This constitutes an elective indication for AS and requires the treating physician to inform the patient of the available data on renal tumor growth kinetics, with limitations and the uncertain longterm risk of progression. No matter what the indication for AS of a renal mass, it must be understood that the patient and physician are both taking a calculated risk due to the heterogeneous and occasional unpredictable behavior of RCC.

In summary, quantification of a patient’s perioperative risk as well as competing risks of death must be thoughtfully integrated into clinical decision making. Current ubiquitous qualitative approaches must be replaced by quantitative strategies. Given the known yearly growth rates of SRMs [14] and the low likelihood of developing metastatic RCC in masses less than 4 cm when followed for 24–30 months [14, 29], AS is a reasonable treatment strategy in the elderly or patients with severe medical comorbidities.

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