Temporal trends of the disease burden of renal cell carcinoma from 1992 to 2019 in the US: A population-based analysis

Temporal trends of the disease burden of renal cell carcinoma from 1992 to 2019 in the US: A population-based analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Temporal trends of the disease burden of renal cell carcinoma from 1992 to 2019 in the US: A population-based analysis Ruyan Chen, Tian Tang, Jianglong Han, Si Li, Wenmin Liu, Haiyu Deng, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4113494/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 May, 2025 Read the published version in Cancer Causes & Control → Version 1 posted 7 You are reading this latest preprint version Abstract Purpose Significant advances in the management, in particular the treatment, of renal cell carcinoma (RCC) has have been made over the years. However, it is not clear whether these advances reduce the disease burden of RCC at the population level. Methods Using data from the Surveillance, Epidemiology, and End Results database, we estimated the temporal trends of RCC incidence, incidence-based mortality (IBM), and survival rates in the United States (US) from 1992 to through 2019. Results From 2008 to 2019, the incidence increased slowly at 1.1% annually (95% CI: 0.6–1.5%). The overall IBM rate of RCC increased by 6.8% per year (95% CI: -1.1–15.3%) between 1994 and 1997, plateaued between 1997 and 2015, and then decreased nonsignificantly after 2015. During the study period, the overall 5-year survival rate of RCC continuously increased from 53.69% in 1992 to 72.90% in 2014, with the best improvement observed for RCC patients with distant disease. However, we projected that, given the current trends, the incidence of RCC in the US will continue to increase from 6.92 per 100,000 in 2015–2019 to 9.59 per 100,000 in 2040–2044. Conclusion Over the years, the mortality of RCC has been decreased reducing at the US populational level mainly because the considerably significantly improved survival of RCC patients at all stages through the advances in treatment. However, the overall incidence of RCC is continuously increasing, indicating that more effective preventive strategies should be developed to reduce the disease burden of RCC. Kidney cancer Trends Incidence-based mortality (IBM) Surveillance Epidemiology and End Results (SEER) age-period-cohort analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction In 2023, kidney cancer was the seventh most common cancer and the eleventh leading cause of cancer deaths, with an estimated 81,800 new cases and 14,890 deaths in the United States (US) [ 1 ]. Renal cell carcinoma (RCC), originating from the renal parenchymal epithelium, accounts for more than 90% of kidney cancers [ 2 ]. Globally, RCC mortality began to plateau or decline in many countries until the mid-1990s, after rising for more than two consecutive decades from the late 1970s [ 3 ]. It was reported that the incidence of RCC in US has increased continuously since 1990, especially for early disease [ 4 ]. However, it is not clear whether the increase in early-stage RCC is driven by a real increase in the overall RCC incidence or by stage migration through advances in early diagnosis [ 5 , 6 ]. Over the years, the promotion of abdominal imaging has led to more RCC patients being diagnosed at an earlier stage [ 4 ]. Based on the Surveillance, Epidemiology, and End Results (SEER) database, Sun et al. reported that the prevalence of localized disease increased (51.2 to 70.8%), and the prevalence of both regional stage (20.9 to 13.6%) and distant stage (27.9 to 15.6%) declined from 1988 to 2006 [ 6 ]. In addition, the median tumor size decreased between 2001 and 2016 (from 50 mm to 45 mm in men and from 49 mm to 40 mm in women; p < 0.001) [ 5 ]. The observed stage migration at the population level may reflect an upward trend in the increased incidence of early-stage RCC. However, Saad et al. found an increase in the incidence of all stages of RCC between 1992 and 2015, except for unclassified disease [ 7 ]. The study by Palumbo et al. further supported an increase in the incidence of both early-stage and late-stage RCC between 2001 and 2016 [ 5 ], which suggested that the increased incidence of RCC might also be attributed to the prevalence of RCC risk factors, such as smoking, obesity, hypertension, and a history of chronic kidney disease [ 3 , 5 , 7 ]. In recent decades, the prevalence of risk factors for RCC has changed considerably in the US because of smoking cessation and better management of hypertension in the general population [ 8 – 12 ]. However, overweight and metabolic disorders are currently more prevalent in the US population [ 13 – 16 ]. These changing factors also influence the current and future incidence of RCC. On the other hand, continuous advances in the diagnosis and treatment of RCC further improve the survival and thus reduce the mortality of RCC [ 17 ]. To gain insight into RCC prevention and treatment, it is necessary to evaluate the latest trends in the RCC burden at the US population level. Therefore, we analyzed the incidence, mortality, and survival of patients with kidney cancer in the US from 1992 to 2019 based on the SEER database. Materials and methods Data source The SEER database of the National Cancer Institute (NCI) is a public cancer registry database that covers approximately 26% of the US population [ 18 ]. Cancer cases are collected by the SEER program from health service unit records and death certificates of residents when cancer is listed as a cause of death. The population at risk for the incidence and incidence-based mortality (IBM) was the exposed population in the SEER area during the same period. We used SEER*Stat software (version 8.4.1) to select patients (aged at least 20 years) diagnosed with RCC from the SEER-13 registry database from 1992 to 2019. RCC cases were defined according to the third revision of the International Classification of Diseases for Oncology and were classified as papillary adenocarcinoma (8260/3), clear cell adenocarcinoma (8310/3), renal cell carcinoma (8312/3), renal cell carcinoma, chromophobe type (8317/3), and collecting duct carcinoma (8319/3) [ 19 ]. Patients diagnosed by death certificate or autopsy only were excluded due to incomplete histology information. Patients with multiple primary cancers or kidney cancer as a secondary cancer were also excluded from this study. Joinpoint regression Joinpoint regression analysis was performed using the NCI Joinpoint Regression Program (version 4.9.1.0), which describes piecewise log-linear calendar trends in age-adjusted rates by sex, histology, and stage. We used a best-fitting log-linear regression model to calculate the annual percent change (APC) and the corresponding 95% confidence interval (CI) for each calendar period and to identify the joinpoints for significant changes in the APC ( P < 0.05). Age-period-cohort model Age-period-cohort analysis assesses and estimates the influence of age, calendar year (period), and year of birth (cohort) on disease incidence or mortality rates. Using the age-period-cohort model provided by the NCI web tools [ 20 ], we assessed the relationship between the observed rates and age, period, and cohort effects. The incidence and IBM of RCC were calculated using thirteen 5-year age groups (20–24, 25–29, …, 80–84) and five corresponding calendar periods. We calculated the rate ratio (RR) of the incidence and IBM for each calendar period (or birth cohort) to the reference period (or birth cohort), adjusting for age and nonlinear cohort (or birth cohort) effects. A P value ≤ 0.05 (two-tailed) was considered statistically significant. Future projections We employed the nordpred package in R language (version 3.5.1) to predict the incidence and IBM rates of RCC in US from 2019 to 2044 [ 21 ]. The pertinent future population projection data was sourced from the World Population Prospects published by the United Nations [ 22 ]. Results Trends in RCC incidence in the US From 1992 to 2019, the incidence of RCC increased consistently regardless of sex or age group (Table 1 ). The overall incidence of RCC increased from 8.90 per 100,000 in 1992 to 14.53 per 100,000 in 2019 (Fig. 1 A). The incidence of clear-cell RCC increased from 1.27 per 100,000 in 1992 to 9.31 per 100,000 in 2019 (average annual percent change [AAPC] = 7.9%, 95% CI: 6.2–9.6%) (Fig. 1 B). Temporal trends in the incidence were significantly different by stage (Fig. 1 C). The incidence of localized disease increased from 4.54 per 100,000 in 1992 to 9.96 per 100,000 in 2019 (AAPC = 3.5%, 95% CI: 3.1–3.9%). The incidence of regional disease increased from 1.88 per 100,000 in 1992 to 2.50 per 100,000 in 2019 (APC = 1.0%, 95% CI: 0.7–1.4%). Table 1 Joinpoint trends of RCC incidence rates, SEER-13 registries a , 1992–2019. Joinpoint trends for incidence rates Trend 1 Trend 2 Trend 3 1992–2019 AAPC Characteristic Years APC (95% CI) p Years APC (95% CI) p Years APC (95% CI) p AAPC (95% CI) p Overall 1992–2008 2.8* (2.4 to 3.1) < 0.001 2008–2019 1.1*(0.6 to 1.5) < 0.001 — — — 2.1*(1.8–2.3) < 0.001 Male 1992–2008 2.5* (2.1 to 2.9) < 0.001 2008–2019 1.2*(0.7 to 1.7) < 0.001 — — — 2.0*(1.7–2.3) < 0.001 Female 1992–2007 3.1* (2.5 to 3.7) < 0.001 2007–2019 0.8*(0.1 to 1.4) 0.020 — — — 2.1*(1.6–2.5) < 0.001 Age groups 20-24 b — — — — — — — — — — — 25–29 1992–1996 -14.0(-33.3 to 10.8) 0.228 1996–2011 9.9* (6.2 to 13.8) < 0.001 2011–2019 -2.3(-7.3 to 3.0) 0.373 2.4(-1.9 to 6.8) 0.279 30–34 1992–2015 6.4*(5.1 to 7.6) < 0.001 2015–2019 -7.9(-18.5 to 4.0) 0.175 4.1*(2.1 to 6.2) < 0.001 35–39 1992–2019 4.6*(4.1 to 5.2) < 0.001 — — — — — — 4.6*(4.1 to 5.2) < 0.001 40–44 1992–2019 4.0*(3.6 to 4.4) < 0.001 — — — — — — 4.0*(3.6 to 4.4) < 0.001 45–49 1992–2009 3.5*(2.7 to 4.2) < 0.001 2009–2019 1.3*(0.0 to 2.5) 0.049 — — — 2.6*(2.0 to 3.3) < 0.001 50–54 1992–2019 2.0*(1.6 to 2.4) < 0.001 — — — — — — 2.0*(1.6 to 2.4) < 0.001 55–59 1992–2019 1.6*(1.3 to 1.9) < 0.001 — — — — — — 1.6*(1.3 to 1.9) < 0.001 60–64 1992–2008 2.8*(2.4 to 3.2) < 0.001 2008–2011 -2.8(-9.6 to 4.6) 0.430 2011–2019 1.7*(1.0 to 2.5) < 0.001 1.8*(1.0 to 2.7) < 0.001 65–69 1992–2007 2.9*(2.3 to 3.6) < 0.001 2007–2019 0.7(0.1 to 1.3) 0.031 — — — 1.9*(1.5 to 2.3) < 0.001 70–74 1992–2019 1.5*(1.2 to 1.9) < 0.001 — — — — — — 1.5*(1.2 to 1.9) < 0.001 75–79 1992–2007 2.7*(2.0 to 3.5) < 0.001 2007–2019 0.8(0.0 to 1.7) 0.057 — — — 1.9*(1.3 to 2.4) < 0.001 80–84 1992–2008 1.5*(0.9 to 2.0) < 0.001 — — — — — — 1.5*(0.9 to 2.0) < 0.001 a SEER-13 Registry areas: San Francisco, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle, Utah, Atlanta, San Jose, Los Angeles, Georgia. b Because zero new cases occurred in the 20–24 age group in 2003, the trend of incidence was not available. * The trend was statistically different from zero ( P < 0.05). Abbreviations: AAPC: average annual percent change; APC: annual percent change; CI: confidence interval; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results; Trends of incidence-based mortality in the US Contradictory to the consistently increasing incidence rates, the IBM of RCC patients were stable from 1997 to 2015 and started to decrease at -2.9% (95% CI: -7.8% to 2.4%) per year thereafter ( Figure 2A, Table 2 ). The IBM of clear cell RCC increased from 0.29 per 100,000 in 1994 to 1.65 per 100,000 in 2015 and decreased at an annual rate of -4.9% (95% CI: -9.2% to -0.4%) after 2015 ( Figure 2B ). However, the IBM for nonclear cell RCC continuously increased from 1996 to 2019 (0.01 per 100,000 to 0.20 per 100,000, AAPC=15.0%, p < 0.001). In contrast, the IBM for unclassified RCC declined from 2.18 per 100,000 in 1994 to 1.00 per 100,000 in 2019, with a peak of 2.70 per 100,000 in 1998. The IBM for both localized RCC and regional RCC showed an increasing or stable trend from 1994 to 2019 ( Figure 2C ). However, the IBM for distant RCC patients dropped from 1.85 per 100,000 in 1998 to 1.27 per 100,000 in 2019. From 1998 to 2004, the IBM of distant RCC decreased at a rate of -4.2% per year (95% CI: -7.8% to -0.5%), and after a plateau period of 11 years, it began to decline again in 2015 with an APC of -5.2% (95% CI: -9.9% to -0.3%). Table 2. Joinpoint trends of RCC IBM rates, SEER-13 a , 1992–2019. Joinpoint trends for IBM raresb Trend 1 Trend 2 Trend 3 1992-2019 AAPC Characteristic Years APC (95% CI) p Years APC (95% CI) p Years APC (95% CI) p AAPC (95% CI) p Overall 1994-1997 6.8(-1.1 to 12.3) 0.088 1997-2015 -0.2(-0.6 to 0.3) 0.404 2015-2019 -2.9( -6.6 to 0.9) 0.124 0.2(-0.9 to 1.3) 0.742 Male 1994-1998 4.8(-2.2 to 12.3) 0.171 1998-2015 0.0(-0.7 to 0.7) 0.980 2015-2019 -2.8(-7.8 to 2.4) 0.265 0.3(-1.1 to 1.7) 0.684 Female 1994-1997 6.5(-1.3 to 14.9) 0.100 1997-2015 -0.8*(-1.2 to -0.4) < 0.001 2017-2019 -8.3( -19.6 to 4.6) 0.183 -0.6(-1.9 to 0.7) 0.378 Age groups 20-24c — — — — — — — — — — — 25-29c — — — — — — — — — — — 30-34c — — — — — — — — — — — 35-39 1994-2019 0.7(-1.4 to 2.7) 0.510 — — — — — — 0.7(-1.4 to 2.7) 0.510 40-44 1994-2019 -1.6*(-2.9 to -0.3) 0.019 — — — — — — -1.6*(-2.9 to -0.3) 0.019 45-49 1994-2019 -1.8*(-2.9 to -0.6) 0.004 — — — — — — -1.8*(-2.9 to -0.6) 0.004 50-54 1994-2019 -1.7*(-2.5 to -0.9) < 0.001 — — — — — — -1.7*(-2.0 to -0.6) 0.001 55-59 1994-2019 -1.5*(-2.2 to -1.1) < 0.001 — — — — — — -1.5*(-2.2 to -1.1) < 0.001 60-64 1994-1998 13.3*(0.8 to 27.3) 0.037 1998-2019 -2.4*(-3.1 to -1.6) < 0.001 — — — 0.0(-1.8 to 1.9) 0.992 65-69 1994-2019 -0.1(-0.7 to 0.4) 0. 026 — — — — — — -0.1(-0.7 to 0.4) 0.602 70-74 1994-2017 0.8* (0.2 to 1.4) 0.011 2017-2019 -12.5(-30.6 to 10.2) 0.241 — — — -0.3(-2.1 to 1.5) 0.708 75-79 1994-2019 0.5(-0.3 to 1.2) 0.189 — — — — — — 0.5(-0.3 to 1.2) 0.189 80-84 1994-2014 2.5*(1.5 to 3.5) < 0.001 2014-2019 -5.0(-11.3 to 1.7) 0.133 — — — 0.9(-0.6 to 2.5) 0.219 a SEER-13 Registry areas: San Francisco, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle, Utah, Atlanta, San Jose, Los Angeles, Georgia. b Joinpoint trends for IBM were analyzed during 1994-2019 after accounting for 2-year burn-in period to catch enough death cases in SEER-13 Registries. c Because deaths in the 20-24, 25-29 age grbaoups were not consecutive from 1994 to 2019, the trend of IBM was not available. * The trend was statistically different from zero ( P < 0.05). Abbreviations: AAPC: average annual percent change; APC: annual percent change; CI: confidence interval; IBM: incidence-based mortality; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results; Survival trends of RCC patients in the US The 5-year survival rates for RCC patients in the US increased consistently from 53.69% in 1992 to 72.90% in 2014 ( Figure 3A ). The 5-year survival rates of clear cell RCC increased from 64.44% in 1992 to 78.11% in 2014, with an AAPC of 0.9% (95% CI: 0.6% to 1.2%) ( Figure 3B ). The 5-year survival rates of nonclear cell RCC increased from 63.64% in 1992 to 85.72% in 2014 at a rate of 0.6% per year ( p = 0.002). The 5-year survival rates of unclassified RCC decreased slightly with an APC of -0.5% ( p < 0.001). From 1992 to 2019, the proportion of unclassified RCC decreased significantly from 84.94% to 18.09%, while those of clear cell RCC (14.43% in 1992 to 64.04% in 2019) and nonclear cell RCC (0.63% in 1992 to 17.87% in 2019) both increased greatly. The survival rate of RCC patients increased consistently between 1998 and 2018 at all stages ( Figure 3E-H ). The 1-year survival of distant disease increased from 31.15% in 1992 to 52.87% in 2006 (APC = 2.5%, 95% CI: 1.3% to 3.8%), increasing rapidly by 6.4% (95% CI: -1.8% to 15.3%) from 2015 to 2018. From 1992 to 2019, the proportion of regional, distant, and unstaged disease decreased, except for localized disease ( Figure 3D ). The proportion of localized disease increased from 51.15% to 67.67%, with almost two-thirds of RCC patients in the localized stage. The proportion of distant disease decreased from 21.95% to 13.03%. Age-period-cohort analysis and projections The age-period-cohort analysis of the incidence and IBM of RCC patients in the US is shown in Figure 4 . Incidence rates increased over time in all age groups ( Figure 4A, B ). IBM rates were stable or decreased in most age groups ( Figure 4E, F ). The incidence of RCC increased with the progression of the study period ( Figure 4C ). The period effect analysis showed that the rate ratio (RR) of IBM declined from 1999-2003 to 2014-2018 ( Figure 4G ). The incidence in the US increased with the aging of the birth cohorts ( Figure 4D ). The cohort effect analysis showed that the risk of death from RCC was the highest among patients born in 1939, and the risk of death gradually decreased with the aging of the birth cohort ( Figure 4H ). Compared with patients born in 1954, the cohort RR for patients born in 1994 was approximately 80% lower in terms of RCC IBM rates, with the lowest risk of death. Figure 5 shows the projections of future trends in the incidence and IBM of RCC in the US until 2044. Over the next 25 years, the incidence of RCC in the US will continue to increase from 6.92 per 100,000 in 2015-2019 to 9.59 per 100,000 in 2040-2044 ( Figure 5A ). The IBM of the RCC population in the US will decline slowly from 1.95 per 100,000 in 2015-2019 to 1.75 per 100,000 in 2040-2044 ( Figure 5B ). For most age groups, the incidence will continue to increase over the next 25 years, while the IBM will decline or remain stable (Figure 5C, D ). Discussion In this study, we found that the overall IBM rate of RCC has remained stable or decreased since 1997 because of the significantly improved survival of patients. This trend could be attributed mainly to treatment (tertiary prevention) advances, and to a lesser degree, better secondary prevention that detects more early-stage diseases. However, the incidence of RCC has not yet started to decrease. In contrast, the incidence is predicted to continue to increase over the next 25 years, unless more effective primary prevention strategies are implemented. We found that the incidence of RCC has been increasing since 1992 in the US, especially among males. Two Global Burden of Disease (GBD) studies showed that since the 1990s, the RCC incidence has increased in most countries, including the US, and the increase is more marked among males than among females [3, 23]. Saad et al. found that the incidence of RCC among females began to decline after 2008, whereas the incidence of RCC among males increased [7]. Although we did not observe a downward trend in the RCC incidence for females, we did find that the incidence has remained stable. Furthermore, we project that the incidence of RCC will continue to increase through 2043. The increasing incidence of RCC calls for successful primary prevention of RCC, especially in controlling modifiable risk factors such as smoking, obesity, and hypertension [4]. The prevalence of hypertension among US adults has not changed substantially during the past two decades [9, 12]. Therefore, hypertension might not account for the increasing incidence of RCC in the US. Recent studies have shown that because of success in smoking cessation initiatives, the number of smokers in the US has decreased considerably in the last 20 years [8, 10-11]. A reduction in the smoking-related disease burden has already been seen in the US population [24]. Thus, the increasing RCC incidence in the US is not attributable to smoking. Interestingly, we found that the RCC incidence among males was approximately twice as high as that among females in recent years. Since 2007, the increase in the incidence of overall RCC has been dominated by an increase in the incidence of RCC among males. Coincidentally, the age-adjusted prevalence of general obesity was reported to have increased more among males than among females in the US population from 2001 to 2018 [15]. Obesity is an independent risk factor for RCC [25] and is estimated to account for 26% of RCC cases worldwide [26]. The prevalence of obesity in the US remains high and has been increasing since 1999, with nearly half of US adults projected to be obese by 2030 [13-14, 16]. Therefore, the increasing prevalence and the same sex difference in obesity suggest that the increasing incidence of RCC is probably attributed to rising obesity rates in the US population, especially among males. Thus, to reduce the burden of RCC in the US, it is prudent to recommend that both individuals and society make a concerted effort to fight against obesity. Individuals should develop healthy behaviors and lifestyles and exercise and have a healthy diet [27, 28]. At the same time, we should further strengthen social health education and develop and implement stronger public policies, such as building more public sports venues [29]. We projected that the incidence of RCC will continue to increase over the next 25 years for most age groups; therefore, these strategies should be applied to people of all ages. We found that the increasing incidence was predominantly for localized disease, with decreasing incidence in both regional stage and distant disease. Since 1992, the proportion of localized disease has increased substantially. Localized disease currently accounts for almost two-thirds of RCC cases. In contrast, the proportions of distant and unstaged disease both decreased by half from 1992 to 2019. This is obviously attributed to the more widespread application and advances in early diagnostic measures such as abdominal imaging and examinations [30-31], which allow more incidental detection and early diagnosis of small cancerous lesions [32-33]. Early diagnosis allows potential distant RCC patients to be diagnosed at an early stage and prevents stage migration for RCC. Secondary prevention (early detection and early diagnosis) and early treatment together can prolong the survival of RCC patients and improve their long-term quality of life. To achieve comprehensive secondary prevention, the main approach is to conduct disease screening [34]. For individuals, regular health checkups might help. Public health authorities should develop relevant policies, such as providing more available health management and even free regular health checkups for people over 65 years of age with a high prevalence of RCC. In the 1990s, distant RCC patients were treated with interferon-α (IFN-α) and interleukin-2 (IL-2) alone or in combination, with poor patient survival. The results of two prospective trials, EORTC 30947 and SWOG 8949, showed that IFN-α combined with nephrectomy significantly improved overall survival (OS) in advanced RCC, which established the use of nephrectomy for patients with advanced RCC [35-37]. The decrease in the IBM of distant RCC from 1998 to 2004 was associated with the introduction of this therapy. In the period analysis of IBM, the mortality risk for RCC began to decrease from 1999-2003, further illustrating that this treatment combination can reduce the risk of death from RCC. Our data also showed that the IBM among distant RCC patients started decreasing significantly in 2015. In 2015, the first immune checkpoint inhibitor (ICI), nivolumab, was used to treat RCC [38]. Subsequently, ICI-based immune combination therapies such as avelumab combined with axitinib, pembrolizumab combined with axitinib, and nivolumab combined with ipilimumab have shown significant clinical efficacy [39-41]. Immunotherapy has ushered in a new era in the treatment of RCC and improved the clinical outcomes of patients with advanced RCC [42]. Ongoing trials of combination therapy have provided potential for durable clinical benefit in the survival of RCC patients. For example, a recent trial (COSMIC-313) showed superior efficacy of the triple combination of cabozantinib, nivolumab, and ipilimumab in patients with metastatic RCC [43]. However, the SEER database lacks information on RCC risk factors, such as lifestyle factors, environmental exposures, and viral infection status, so we could not directly explain the direct association between individual exposure factors and RCC incidence. Thus, the association could only be inferred indirectly by investigating the trend of RCC risk factors. In addition, a large number of cases were described with unknown histology in SEER; thus, the incidence and IBM trends could not be reliably analyzed by histological subtype in this study. Nevertheless, the SEER database collects cancer diagnosis, treatment, and survival data for approximately 30% of the U.S. population, and population-based cancer registry reporting is considered the gold standard for reporting cancer rates in specific populations. Although descriptive studies cannot provide absolute evidence of causality, the findings of this study can help inform the prevention of RCC to guide the rational allocation of health resources and the targeted development of preventive intervention strategies. Conclusion Treatment advances have remarkably improved the survival and moderately reduced the mortality of RCC in the US at the population level. However, the overall incidence of RCC in the US is still increasing, likely due to the rising prevalence of obesity in the US population. We projected that over the next 25 years, the incidence of RCC in the US will continue to increase if no further strengthened strategies are taken. To significantly decrease the disease burden, effective approaches to control modifiable RCC risk factors such as obesity, hypertension and smoking must be further developed and implemented immediately. Abbreviations AAPC average annual percent change APC annual percent change CI confidence interval GBD Global Burden of Disease IBM incidence-based mortality ICI immune checkpoint inhibitor IFN-α interferon-α IL-2 interleukin-2 NCI National Cancer Institute OS overall survival RCC renal cell carcinoma RR rate ratio SEER Surveillance, Epidemiology and End Results US United States. Declarations Funding This work was supported by the National Natural Science Foundation of China (No. 81773555). Declarations of interest The authors have no relevant financial or non-financial interests to disclose. Acknowledgement We sincerely thank the National Cancer Institute and the SEER staff for providing this invaluable database. Author Contributions Conceptualization: Z.F. Data curation: R.C and W.L. Formal analysis: W.L. Funding acquisition: Z.F. Investigation: S.L. H.D. and T.J. Methodology: J.H. Project administration: T.T. Resources: S.L. and W.L. Software: H.D. and T.J. Supervision: T.T. Validation: J.H. Visualization: R.C. and Si Li. Roles/Writing – original draft: R.C. Writing – review & editing: Z.F. and R.C. The work reported in the paper has been performed by the authors, unless clearly specified in the text. Ethical approval and consent to participate Patient consents were not required because the study is a retrospective database research in nature, there was no direct patient contact. Institutional Review Board approval was not required according to our institution policy. 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MMWR Morb Mortal Wkly Rep . Oct 16 2015;64(40):1129-35. doi:10.15585/mmwr.mm6440a1 Sakuma KK, Pierce JP, Fagan P, et al. Racial/Ethnic Disparities Across Indicators of Cigarette Smoking in the Era of Increased Tobacco Control, 1992-2019. Nicotine Tob Res . May 24 2021;23(6):909-919. doi:10.1093/ntr/ntaa231 Yoon SS, Gu Q, Nwankwo T, Wright JD, Hong Y, Burt V. Trends in blood pressure among adults with hypertension: United States, 2003 to 2012. Hypertension . Jan 2015;65(1):54-61. doi:10.1161/hypertensionaha.114.04012 Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in Obesity and Severe Obesity Prevalence in US Youth and Adults by Sex and Age, 2007-2008 to 2015-2016. JAMA . Apr 24 2018;319(16):1723-1725. doi:10.1001/jama.2018.3060 Liu B, Du Y, Wu Y, Snetselaar LG, Wallace RB, Bao W. Trends in obesity and adiposity measures by race or ethnicity among adults in the United States 2011-18: population based study. BMJ . Mar 16 2021;372:n365. doi:10.1136/bmj.n365 Sun JY, Huang WJ, Hua Y, et al. Trends in general and abdominal obesity in US adults: Evidence from the National Health and Nutrition Examination Survey (2001-2018). Front Public Health . 2022;10:925293. doi:10.3389/fpubh.2022.925293 Wang Y, Beydoun MA, Min J, Xue H, Kaminsky LA, Cheskin LJ. Has the prevalence of overweight, obesity and central obesity levelled off in the United States? Trends, patterns, disparities, and future projections for the obesity epidemic. Int J Epidemiol . Jun 1 2020;49(3):810-823. doi:10.1093/ije/dyz273 Capitanio U, Bensalah K, Bex A, et al. Epidemiology of Renal Cell Carcinoma. Eur Urol . Jan 2019;75(1):74-84. doi:10.1016/j.eururo.2018.08.036 National Cancer Institute. Overview of SEER incidence data, 1975-2017. . Accessed May 25, 2023. https://seer.cancer.gov/data/ Organization GWH. International classification of diseases for oncology (‎ICD-O)‎, 3rd ed., 1st revision. Accessed June 25, 2022. https://apps.who.int/iris/handle/10665/96612 Rosenberg PS, Check DP, Anderson WF. A web tool for age-period-cohort analysis of cancer incidence and mortality rates. Cancer Epidemiol Biomarkers Prev . Nov 2014;23(11):2296-302. doi:10.1158/1055-9965.Epi-14-0300 Jürgens V, Ess S, Cerny T, Vounatsou P. A Bayesian generalized age-period-cohort power model for cancer projections. Stat Med . Nov 20 2014;33(26):4627-36. doi:10.1002/sim.6248 United Nations DoEaSA, Population Division. World Population Prospects 2022. Accessed 2022 Dec, 2022. https://population.un.org/wpp/Download/Standard/Population/ Dy GW, Gore JL, Forouzanfar MH, Naghavi M, Fitzmaurice C. Global Burden of Urologic Cancers, 1990-2013. Eur Urol . Mar 2017;71(3):437-446. doi:10.1016/j.eururo.2016.10.008 Parker AS, Cerhan JR, Janney CA, Lynch CF, Cantor KP. Smoking cessation and renal cell carcinoma. Ann Epidemiol . Apr 2003;13(4):245-51. doi:10.1016/s1047-2797(02)00271-5 Macleod LC, Hotaling JM, Wright JL, et al. Risk factors for renal cell carcinoma in the VITAL study. J Urol . Nov 2013;190(5):1657-61. doi:10.1016/j.juro.2013.04.130 Scelo G, Larose TL. Epidemiology and Risk Factors for Kidney Cancer. J Clin Oncol . Oct 29 2018;36(36):Jco2018791905. doi:10.1200/jco.2018.79.1905 Schottenfeld D, Beebe-Dimmer JL, Buffler PA, Omenn GS. Current perspective on the global and United States cancer burden attributable to lifestyle and environmental risk factors. Annu Rev Public Health . 2013;34:97-117. doi:10.1146/annurev-publhealth-031912-114350 Vineis P, Wild CP. Global cancer patterns: causes and prevention. Lancet . Feb 8 2014;383(9916):549-57. doi:10.1016/s0140-6736(13)62224-2 Wild CP. The role of cancer research in noncommunicable disease control. J Natl Cancer Inst . Jul 18 2012;104(14):1051-8. doi:10.1093/jnci/djs262 Kramer MR, Levin DC, Rao VM. Utilization Trends in Abdominal Imaging, 2004-2016. AJR Am J Roentgenol . Aug 2020;215(2):420-424. doi:10.2214/ajr.19.22524 Moreno CC, Hemingway J, Johnson AC, Hughes DR, Mittal PK, Duszak R, Jr. Changing Abdominal Imaging Utilization Patterns: Perspectives From Medicare Beneficiaries Over Two Decades. J Am Coll Radiol . Aug 2016;13(8):894-903. doi:10.1016/j.jacr.2016.02.031 Canvasser NE, Kay FU, Xi Y, et al. Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging to Identify Clear Cell Renal Cell Carcinoma in cT1a Renal Masses. J Urol . Oct 2017;198(4):780-786. doi:10.1016/j.juro.2017.04.089 Lightfoot N, Conlon M, Kreiger N, et al. Impact of noninvasive imaging on increased incidental detection of renal cell carcinoma. Eur Urol . May 2000;37(5):521-7. doi:10.1159/000020188 Franceschi S, Wild CP. Meeting the global demands of epidemiologic transition - the indispensable role of cancer prevention. Mol Oncol . Feb 2013;7(1):1-13. doi:10.1016/j.molonc.2012.10.010 Flanigan RC, Mickisch G, Sylvester R, Tangen C, Van Poppel H, Crawford ED. Cytoreductive nephrectomy in patients with metastatic renal cancer: a combined analysis. J Urol . Mar 2004;171(3):1071-6. doi:10.1097/01.ju.0000110610.61545.ae Flanigan RC, Salmon SE, Blumenstein BA, et al. Nephrectomy followed by interferon alfa-2b compared with interferon alfa-2b alone for metastatic renal-cell cancer. N Engl J Med . Dec 6 2001;345(23):1655-9. doi:10.1056/NEJMoa003013 Mickisch GH, Garin A, van Poppel H, de Prijck L, Sylvester R. Radical nephrectomy plus interferon-alfa-based immunotherapy compared with interferon alfa alone in metastatic renal-cell carcinoma: a randomised trial. Lancet . Sep 22 2001;358(9286):966-70. doi:10.1016/s0140-6736(01)06103-7 Motzer RJ, Escudier B, McDermott DF, et al. Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med . Nov 5 2015;373(19):1803-13. doi:10.1056/NEJMoa1510665 Motzer RJ, Penkov K, Haanen J, et al. Avelumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med . Mar 21 2019;380(12):1103-1115. doi:10.1056/NEJMoa1816047 Motzer RJ, Tannir NM, McDermott DF, et al. Nivolumab plus Ipilimumab versus Sunitinib in Advanced Renal-Cell Carcinoma. N Engl J Med . Apr 5 2018;378(14):1277-1290. doi:10.1056/NEJMoa1712126 Rini BI, Plimack ER, Stus V, et al. Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med . Mar 21 2019;380(12):1116-1127. doi:10.1056/NEJMoa1816714 Braun DA, Bakouny Z, Hirsch L, et al. Beyond conventional immune-checkpoint inhibition - novel immunotherapies for renal cell carcinoma. Nat Rev Clin Oncol . Apr 2021;18(4):199-214. doi:10.1038/s41571-020-00455-z Msaouel P. Less is More? First Impressions From COSMIC-313. Cancer Invest . Jan 2023;41(1):101-106. doi:10.1080/07357907.2022.2136681 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 May, 2025 Read the published version in Cancer Causes & Control → Version 1 posted Editorial decision: Revision requested 12 Apr, 2025 Reviews received at journal 08 Dec, 2024 Reviewers agreed at journal 27 Nov, 2024 Reviewers invited by journal 27 May, 2024 Submission checks completed at journal 17 Mar, 2024 Editor assigned by journal 17 Mar, 2024 First submitted to journal 16 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4113494","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280552098,"identity":"c4ab6feb-5426-4175-bc3d-3d80b377f31b","order_by":0,"name":"Ruyan Chen","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Ruyan","middleName":"","lastName":"Chen","suffix":""},{"id":280552099,"identity":"abc01812-c449-413a-8540-d510e114ef0a","order_by":1,"name":"Tian Tang","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Tang","suffix":""},{"id":280552100,"identity":"8f176481-e107-405f-97fb-6d1cb6977314","order_by":2,"name":"Jianglong Han","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Jianglong","middleName":"","lastName":"Han","suffix":""},{"id":280552101,"identity":"06fd7738-1b94-4cd0-8620-44ba5d3c464d","order_by":3,"name":"Si Li","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Si","middleName":"","lastName":"Li","suffix":""},{"id":280552102,"identity":"f2d981a5-0274-4a1c-9cb1-26c7d608edda","order_by":4,"name":"Wenmin Liu","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Wenmin","middleName":"","lastName":"Liu","suffix":""},{"id":280552103,"identity":"bea359a4-2c07-41fb-a3a6-e14c7d8045d5","order_by":5,"name":"Haiyu Deng","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Haiyu","middleName":"","lastName":"Deng","suffix":""},{"id":280552104,"identity":"27273eb7-d71a-4545-9173-5b84eaeec0b2","order_by":6,"name":"Tingting Jian","email":"","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Jian","suffix":""},{"id":280552105,"identity":"83a2ca6f-24b1-4744-9b5d-bafb10a89daf","order_by":7,"name":"Zhenming Fu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYDCCA0DEYwNkMAPxBxCXgcGACC1pEC2MM4jVwgDWAtLFQ4wWvuNnDA+8SThsr9vOe/i1bdudxAb25m0SDDV3cGqRPJNjcHBOwmFms8N8ada5bc8SG3iOlUkwHHuGU4vBgbSEw7w/DrOZHeYxM87ddjixQSLHTIKx4TBuLeefJRzmASKwFkuQFvk3BLTcSD4A0iIB1GL8mBFsCw9+LZI3Hh8A+iXdAGQLY++/w8ZtPGnFFgnHcGvhO5/Y/OFNgrW92fkzxh9+nDks289+eOONDzW4tSADNgkwCSISiNIAjMkPRCocBaNgFIyCEQYAYjRd6O0UqGUAAAAASUVORK5CYII=","orcid":"","institution":"Renmin Hospital of Wuhan University","correspondingAuthor":true,"prefix":"","firstName":"Zhenming","middleName":"","lastName":"Fu","suffix":""}],"badges":[],"createdAt":"2024-03-16 14:01:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4113494/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4113494/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10552-025-02007-1","type":"published","date":"2025-05-13T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53185082,"identity":"3b7618ef-813d-4fa5-98c6-12d2db2e6e7b","added_by":"auto","created_at":"2024-03-21 16:09:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":241918,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe incidence trends of RCC, SEER-13 registries, 1992-2019\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe line segments of each curve were selected with the joinpoint program, and the percentage associated with each line represents the annual percentage change during the indicated range of years. Asterisks indicate annual percentage changes that are significantly different from zero (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e APC: annual percent change; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results;\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4113494/v1/a5f6f6663ff9d7c3ea0105c8.png"},{"id":53183208,"identity":"a3efcd74-fdb1-411c-94d4-9781cfcf56ad","added_by":"auto","created_at":"2024-03-21 16:01:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":259698,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe IBM trends of RCC, SEER-13 registries, 1992-2019\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe line segments of each curve were selected with the joinpoint program, and the percentage associated with each line represents the annual percentage change during the indicated range of years. The incidence-based mortality (IBM) trend of nonclear cell RCC was calculated from 1996 because of the missing mortality data in 1994-1995. Asterisks indicate annual percentage changes that are significantly different from zero (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eAPC: annual percent change; IBM: incidence-based mortality; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results;\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4113494/v1/7212fdf2356874c52508cd7a.png"},{"id":53183206,"identity":"bb428610-8529-4a57-b122-b055ec22ff85","added_by":"auto","created_at":"2024-03-21 16:01:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":339378,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe survival trends and prevalence of RCC by sex, histology and stage, SEER-13 registries, 1992-2019\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe line segments of each curve were selected with the joinpoint program, and the percentage associated with each line represents the annual percentage change during the indicated range of years. Asterisks indicate annual percentage changes that are significantly different from zero (\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e APC: annual percent change; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results;\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4113494/v1/f96d752abf5d66a2711372fc.png"},{"id":53183210,"identity":"af1d29b1-b840-4fda-b511-225ee7e8d16b","added_by":"auto","created_at":"2024-03-21 16:01:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":495212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge-Period-Cohort analysis of RCC incidence and IBM, SEER-13 registries, 1992-2019\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe age-specific analyses divided by age = 50 years \u003cstrong\u003e(A, B)\u003c/strong\u003e, period rate ratio \u003cstrong\u003e(C)\u003c/strong\u003e, and birth cohort rate ratio\u003cstrong\u003e (D)\u003c/strong\u003e of RCC incidence. The age-specific analyses divided by age = 50 years \u003cstrong\u003e(E, F)\u003c/strong\u003e, period rate ratio \u003cstrong\u003e(G)\u003c/strong\u003e, and birth cohort rate ratio \u003cstrong\u003e(H) \u003c/strong\u003eof RCC IBM. Gray zone indicates 95% CIs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eCI: confidence interval; IBM: incidence-based mortality; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results;\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4113494/v1/2f49e2509fb421154f7b47c6.png"},{"id":53183209,"identity":"efcac2d9-3b15-4f85-ba4e-e4c38a724239","added_by":"auto","created_at":"2024-03-21 16:01:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":291861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLong-term trends and future projections of RCC incidence and IBM in the United States\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eProjected projections of the incidence of RCC in the United States over the next 25 years. \u003cstrong\u003e(B)\u003c/strong\u003e Projected projections of the IBM of RCC in the United States over the next 25 years. \u003cstrong\u003e(C) \u003c/strong\u003eFuture projections of the incidence of RCC by age group in the United States over the next 25 years. \u003cstrong\u003e(D) \u003c/strong\u003eFuture projections of the IBM of RCC by age group in the United States over the next 25 years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eIBM: incidence-based mortality; RCC: renal cell carcinoma;\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4113494/v1/023aa9ffae8ff16458ff121f.png"},{"id":83067803,"identity":"30f9e040-c2aa-47fb-98fb-def22071813f","added_by":"auto","created_at":"2025-05-19 16:06:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2532173,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4113494/v1/10b597ab-77a7-49d8-a72e-4f81d9036799.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Temporal trends of the disease burden of renal cell carcinoma from 1992 to 2019 in the US: A population-based analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 2023, kidney cancer was the seventh most common cancer and the eleventh leading cause of cancer deaths, with an estimated 81,800 new cases and 14,890 deaths in the United States (US) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Renal cell carcinoma (RCC), originating from the renal parenchymal epithelium, accounts for more than 90% of kidney cancers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Globally, RCC mortality began to plateau or decline in many countries until the mid-1990s, after rising for more than two consecutive decades from the late 1970s [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It was reported that the incidence of RCC in US has increased continuously since 1990, especially for early disease [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, it is not clear whether the increase in early-stage RCC is driven by a real increase in the overall RCC incidence or by stage migration through advances in early diagnosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver the years, the promotion of abdominal imaging has led to more RCC patients being diagnosed at an earlier stage [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Based on the Surveillance, Epidemiology, and End Results (SEER) database, Sun et al. reported that the prevalence of localized disease increased (51.2 to 70.8%), and the prevalence of both regional stage (20.9 to 13.6%) and distant stage (27.9 to 15.6%) declined from 1988 to 2006 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, the median tumor size decreased between 2001 and 2016 (from 50 mm to 45 mm in men and from 49 mm to 40 mm in women; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The observed stage migration at the population level may reflect an upward trend in the increased incidence of early-stage RCC. However, Saad et al. found an increase in the incidence of all stages of RCC between 1992 and 2015, except for unclassified disease [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The study by Palumbo et al. further supported an increase in the incidence of both early-stage and late-stage RCC between 2001 and 2016 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], which suggested that the increased incidence of RCC might also be attributed to the prevalence of RCC risk factors, such as smoking, obesity, hypertension, and a history of chronic kidney disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent decades, the prevalence of risk factors for RCC has changed considerably in the US because of smoking cessation and better management of hypertension in the general population [\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, overweight and metabolic disorders are currently more prevalent in the US population [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These changing factors also influence the current and future incidence of RCC. On the other hand, continuous advances in the diagnosis and treatment of RCC further improve the survival and thus reduce the mortality of RCC [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To gain insight into RCC prevention and treatment, it is necessary to evaluate the latest trends in the RCC burden at the US population level. Therefore, we analyzed the incidence, mortality, and survival of patients with kidney cancer in the US from 1992 to 2019 based on the SEER database.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThe SEER database of the National Cancer Institute (NCI) is a public cancer registry database that covers approximately 26% of the US population [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Cancer cases are collected by the SEER program from health service unit records and death certificates of residents when cancer is listed as a cause of death. The population at risk for the incidence and incidence-based mortality (IBM) was the exposed population in the SEER area during the same period. We used SEER*Stat software (version 8.4.1) to select patients (aged at least 20 years) diagnosed with RCC from the SEER-13 registry database from 1992 to 2019. RCC cases were defined according to the third revision of the International Classification of Diseases for Oncology and were classified as papillary adenocarcinoma (8260/3), clear cell adenocarcinoma (8310/3), renal cell carcinoma (8312/3), renal cell carcinoma, chromophobe type (8317/3), and collecting duct carcinoma (8319/3) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Patients diagnosed by death certificate or autopsy only were excluded due to incomplete histology information. Patients with multiple primary cancers or kidney cancer as a secondary cancer were also excluded from this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eJoinpoint regression\u003c/h2\u003e \u003cp\u003eJoinpoint regression analysis was performed using the NCI Joinpoint Regression Program (version 4.9.1.0), which describes piecewise log-linear calendar trends in age-adjusted rates by sex, histology, and stage. We used a best-fitting log-linear regression model to calculate the annual percent change (APC) and the corresponding 95% confidence interval (CI) for each calendar period and to identify the joinpoints for significant changes in the APC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAge-period-cohort model\u003c/h2\u003e \u003cp\u003eAge-period-cohort analysis assesses and estimates the influence of age, calendar year (period), and year of birth (cohort) on disease incidence or mortality rates. Using the age-period-cohort model provided by the NCI web tools [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], we assessed the relationship between the observed rates and age, period, and cohort effects. The incidence and IBM of RCC were calculated using thirteen 5-year age groups (20\u0026ndash;24, 25\u0026ndash;29, \u0026hellip;, 80\u0026ndash;84) and five corresponding calendar periods. We calculated the rate ratio (RR) of the incidence and IBM for each calendar period (or birth cohort) to the reference period (or birth cohort), adjusting for age and nonlinear cohort (or birth cohort) effects. A \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026le;\u0026thinsp;0.05 (two-tailed) was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eFuture projections\u003c/h2\u003e \u003cp\u003eWe employed the nordpred package in R language (version 3.5.1) to predict the incidence and IBM rates of RCC in US from 2019 to 2044 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The pertinent future population projection data was sourced from the \u003cem\u003eWorld Population Prospects\u003c/em\u003e published by the United Nations [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTrends in RCC incidence in the US\u003c/h2\u003e \u003cp\u003eFrom 1992 to 2019, the incidence of RCC increased consistently regardless of sex or age group (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The overall incidence of RCC increased from 8.90 per 100,000 in 1992 to 14.53 per 100,000 in 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The incidence of clear-cell RCC increased from 1.27 per 100,000 in 1992 to 9.31 per 100,000 in 2019 (average annual percent change [AAPC]\u0026thinsp;=\u0026thinsp;7.9%, 95% CI: 6.2\u0026ndash;9.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Temporal trends in the incidence were significantly different by stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). The incidence of localized disease increased from 4.54 per 100,000 in 1992 to 9.96 per 100,000 in 2019 (AAPC\u0026thinsp;=\u0026thinsp;3.5%, 95% CI: 3.1\u0026ndash;3.9%). The incidence of regional disease increased from 1.88 per 100,000 in 1992 to 2.50 per 100,000 in 2019 (APC\u0026thinsp;=\u0026thinsp;1.0%, 95% CI: 0.7\u0026ndash;1.4%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eJoinpoint trends of RCC incidence rates, SEER-13 registries\u003csup\u003ea\u003c/sup\u003e, 1992\u0026ndash;2019.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003eJoinpoint trends for incidence rates\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eTrend 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eTrend 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eTrend 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1992\u0026ndash;2019 AAPC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAAPC (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8* (2.4 to 3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2008\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.1*(0.6 to 1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.1*(1.8\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5* (2.1 to 2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2008\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.2*(0.7 to 1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.0*(1.7\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1* (2.5 to 3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2007\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8*(0.1 to 1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.1*(1.6\u0026ndash;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003eAge groups\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20-24\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;1996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-14.0(-33.3 to 10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1996\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.9* (6.2 to 13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2011\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2.3(-7.3 to 3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.4(-1.9 to 6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4*(5.1 to 7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.9(-18.5 to 4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.1*(2.1 to 6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6*(4.1 to 5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.6*(4.1 to 5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0*(3.6 to 4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.0*(3.6 to 4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5*(2.7 to 4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2009\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.3*(0.0 to 2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.6*(2.0 to 3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0*(1.6 to 2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.0*(1.6 to 2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6*(1.3 to 1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.6*(1.3 to 1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8*(2.4 to 3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2008\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.8(-9.6 to 4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2011\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.7*(1.0 to 2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.8*(1.0 to 2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9*(2.3 to 3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2007\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7(0.1 to 1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.9*(1.5 to 2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5*(1.2 to 1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.5*(1.2 to 1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7*(2.0 to 3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2007\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8(0.0 to 1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.9*(1.3 to 2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u0026ndash;2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5*(0.9 to 2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.5*(0.9 to 2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e SEER-13 Registry areas: San Francisco, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle, Utah, Atlanta, San Jose, Los Angeles, Georgia.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Because zero new cases occurred in the 20\u0026ndash;24 age group in 2003, the trend of incidence was not available.\u003c/p\u003e \u003cp\u003e* The trend was statistically different from zero (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e AAPC: average annual percent change; APC: annual percent change; CI: confidence interval; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrends of incidence-based mortality in the US\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContradictory to the consistently increasing incidence rates, the IBM of RCC patients were stable from 1997 to 2015 and started to decrease at -2.9% (95% CI: -7.8% to 2.4%) per year thereafter (\u003cstrong\u003eFigure 2A, Table 2\u003c/strong\u003e). The IBM of clear cell RCC increased from 0.29 per 100,000 in 1994 to 1.65 per 100,000 in 2015 and decreased at an annual rate of -4.9% (95% CI: -9.2% to -0.4%) after 2015 (\u003cstrong\u003eFigure 2B\u003c/strong\u003e). However, the\u0026nbsp;IBM for nonclear cell RCC continuously increased from 1996 to 2019 (0.01 per 100,000 to 0.20 per 100,000, AAPC=15.0%, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001).\u0026nbsp;In contrast, the IBM for unclassified RCC declined from 2.18 per 100,000 in 1994 to 1.00 per 100,000 in 2019, with a peak of 2.70 per 100,000 in 1998. The IBM for both localized RCC and regional RCC showed an increasing or stable trend from 1994 to 2019 (\u003cstrong\u003eFigure 2C\u003c/strong\u003e). However, the IBM for distant RCC patients dropped from 1.85 per 100,000 in 1998 to 1.27 per 100,000 in 2019. From 1998 to 2004, the IBM of distant RCC decreased at a rate of -4.2% per year (95% CI: -7.8% to -0.5%), and after a plateau period of 11 years, it began to decline again in 2015 with an APC of -5.2% (95% CI: -9.9% to -0.3%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Joinpoint trends of RCC IBM rates, SEER-13\u003csup\u003ea\u003c/sup\u003e, 1992\u0026ndash;2019.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.99638989169675%\" rowspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"87.00361010830325%\" colspan=\"11\" valign=\"top\"\u003e\n \u003cp\u003eJoinpoint trends for IBM raresb\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.65072765072765%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eTrend 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.442827442827443%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eTrend 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.403326403326403%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eTrend 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.503118503118504%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1992-2019 AAPC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003eAPC (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003eAPC (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003eAPC (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003eAAPC (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-1997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e6.8(-1.1 to 12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e1997-2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-0.2(-0.6 to 0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e2015-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e-2.9( -6.6 to 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.2(-0.9 to 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-1998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e4.8(-2.2 to 12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e1998-2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.0(-0.7 to 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e2015-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e-2.8(-7.8 to 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.3(-1.1 to 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-1997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e6.5(-1.3 to 14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e1997-2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-0.8*(-1.2 to -0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e2017-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e-8.3( -19.6 to 4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-0.6(-1.9 to 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003eAge groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e20-24c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e25-29c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e30-34c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e35-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e0.7(-1.4 to 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.7(-1.4 to 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e40-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e-1.6*(-2.9 to -0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-1.6*(-2.9 to -0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e45-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e-1.8*(-2.9 to -0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-1.8*(-2.9 to -0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e50-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e-1.7*(-2.5 to -0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-1.7*(-2.0 to -0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e55-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e-1.5*(-2.2 to -1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-1.5*(-2.2 to -1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e60-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-1998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e13.3*(0.8 to 27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e1998-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-2.4*(-3.1 to -1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.0(-1.8 to 1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e65-69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e-0.1(-0.7 to 0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0. 026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-0.1(-0.7 to 0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e70-74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e0.8* (0.2 to 1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e2017-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-12.5(-30.6 to 10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-0.3(-2.1 to 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e75-79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e0.5(-0.3 to 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.5(-0.3 to 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.949640287769784%\" valign=\"top\"\u003e\n \u003cp\u003e80-84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.014388489208633%\" valign=\"top\"\u003e\n \u003cp\u003e1994-2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.071942446043165%\" valign=\"top\"\u003e\n \u003cp\u003e2.5*(1.5 to 3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.733812949640288%\" valign=\"top\"\u003e\n \u003cp\u003e2014-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e-5.0(-11.3 to 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.374100719424461%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81294964028777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.352517985611511%\" valign=\"top\"\u003e\n \u003cp\u003e0.9(-0.6 to 2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.83453237410072%\" valign=\"top\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e SEER-13 Registry areas: San Francisco, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle, Utah, Atlanta, San Jose, Los Angeles, Georgia.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Joinpoint trends for IBM were analyzed during 1994-2019 after accounting for 2-year burn-in period to catch enough death cases in SEER-13 Registries.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Because deaths in the 20-24, 25-29 age grbaoups were not consecutive from 1994 to 2019, the trend of IBM was not available.\u003c/p\u003e\n\u003cp\u003e* The trend was statistically different from zero (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e AAPC: average annual percent change; APC: annual percent change; CI: confidence interval; IBM: incidence-based mortality; RCC: renal cell carcinoma; SEER: Surveillance, Epidemiology and End Results;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurvival trends of RCC patients in the US\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 5-year survival rates for RCC patients in the US increased consistently from 53.69% in 1992 to 72.90% in 2014 (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). The 5-year survival rates of clear cell RCC increased from 64.44% in 1992 to 78.11% in 2014, with an AAPC of 0.9% (95% CI: 0.6% to 1.2%) (\u003cstrong\u003eFigure 3B\u003c/strong\u003e). The 5-year survival rates of nonclear cell RCC increased from 63.64% in 1992 to 85.72% in 2014 at a rate of 0.6% per year (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.002). The 5-year survival rates of unclassified RCC decreased slightly with an APC of -0.5% (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). From 1992 to 2019, the proportion of unclassified RCC decreased significantly from 84.94% to 18.09%, while those of clear cell RCC (14.43% in 1992 to 64.04% in 2019) and nonclear cell RCC (0.63% in 1992 to 17.87% in 2019) both increased greatly. The survival rate of RCC patients increased consistently between 1998 and 2018 at all stages (\u003cstrong\u003eFigure 3E-H\u003c/strong\u003e). The 1-year survival of distant disease increased from 31.15% in 1992 to 52.87% in 2006 (APC = 2.5%, 95% CI: 1.3% to 3.8%), increasing rapidly by 6.4% (95% CI: -1.8% to 15.3%) from 2015 to 2018. From 1992 to 2019, the proportion of regional, distant, and unstaged disease decreased, except for localized disease (\u003cstrong\u003eFigure 3D\u003c/strong\u003e). The proportion of localized disease increased from 51.15% to 67.67%, with almost two-thirds of RCC patients in the localized stage. The proportion of distant disease decreased from 21.95% to 13.03%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge-period-cohort analysis and projections\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe age-period-cohort analysis of the incidence and IBM of RCC patients in the US is shown in\u003cstrong\u003e\u0026nbsp;Figure 4\u003c/strong\u003e. Incidence rates increased over time in all age groups (\u003cstrong\u003eFigure 4A, B\u003c/strong\u003e). IBM rates were stable or decreased in most age groups (\u003cstrong\u003eFigure 4E, F\u003c/strong\u003e). The incidence of RCC increased with the progression of the study period (\u003cstrong\u003eFigure 4C\u003c/strong\u003e). The period effect analysis showed that the rate ratio (RR) of IBM declined from 1999-2003 to 2014-2018 (\u003cstrong\u003eFigure 4G\u003c/strong\u003e). The incidence in the US increased with the aging of the birth cohorts (\u003cstrong\u003eFigure 4D\u003c/strong\u003e). The cohort effect analysis showed that the risk of death from RCC was the highest among patients born in 1939, and the risk of death gradually decreased with the aging of the birth cohort (\u003cstrong\u003eFigure 4H\u003c/strong\u003e). Compared with patients born in 1954, the cohort RR for patients born in 1994 was approximately 80% lower in terms of RCC IBM rates, with the lowest risk of death. \u003cstrong\u003eFigure 5\u003c/strong\u003e shows the projections of future trends in the incidence and IBM of RCC in the US until 2044. Over the next 25 years, the incidence of RCC in the US will continue to increase from 6.92 per 100,000 in 2015-2019 to 9.59 per 100,000 in 2040-2044 (\u003cstrong\u003eFigure 5A\u003c/strong\u003e). The IBM of the RCC population in the US will decline slowly from 1.95 per 100,000 in 2015-2019 to 1.75 per 100,000 in 2040-2044 (\u003cstrong\u003eFigure 5B\u003c/strong\u003e). For most age groups, the incidence will continue to increase over the next 25 years, while the IBM will decline or remain stable \u003cstrong\u003e(Figure 5C, D\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we found that the overall IBM rate of RCC has remained stable or decreased since 1997 because of the significantly improved survival of patients. This trend could be attributed mainly to treatment (tertiary prevention) advances, and to a lesser degree, better secondary prevention that detects more early-stage diseases. However, the incidence of RCC has not yet started to decrease. In contrast, the incidence is predicted to continue to increase over the next 25 years, unless more effective primary prevention strategies are implemented.\u003c/p\u003e\n\u003cp\u003eWe found that the incidence of RCC has been increasing since 1992 in the US, especially among males. Two Global Burden of Disease (GBD) studies showed that since the 1990s, the RCC incidence has increased in most countries, including the US, and the increase is more marked among males than among females [3, 23]. Saad et al. found that the incidence of RCC among females began to decline after 2008, whereas the incidence of RCC among males increased [7]. Although we did not observe a downward trend in the RCC incidence for females, we did find that the incidence has remained stable. Furthermore, we project that the incidence of RCC will continue to increase through 2043. The increasing incidence of RCC calls for successful primary prevention of RCC, especially in controlling modifiable risk factors such as smoking, obesity, and hypertension [4]. The prevalence of hypertension among US adults has not changed substantially during the past two decades [9, 12]. Therefore, hypertension might not account for the increasing incidence of RCC in the US. Recent studies have shown that because of success in smoking cessation initiatives, the number of smokers in the US has decreased considerably in the last 20 years [8, 10-11]. A reduction in the smoking-related disease burden has already been seen in the US population [24]. Thus, the increasing RCC incidence in the US is not attributable to smoking.\u003c/p\u003e\n\u003cp\u003eInterestingly, we found that the RCC incidence among males was approximately twice as high as that among females in recent years. Since 2007, the increase in the incidence of overall RCC has been dominated by an increase in the incidence of RCC among males. Coincidentally, the age-adjusted prevalence of general obesity was reported to have increased more among males than among females in the US population from 2001 to 2018 [15]. Obesity is an independent risk factor for RCC [25] and is estimated to account for 26% of RCC cases worldwide [26]. The prevalence of obesity in the US remains high and has been increasing since 1999, with nearly half of US adults projected to be obese by 2030 [13-14, 16]. Therefore, the increasing prevalence and the same sex difference in obesity suggest that the increasing incidence of RCC is probably attributed to rising obesity rates in the US population, especially among males. Thus, to reduce the burden of RCC in the US, it is prudent to recommend that both individuals and society make a concerted effort to fight against obesity. Individuals should develop healthy behaviors and lifestyles and exercise and have a healthy diet [27, 28]. At the same time, we should further strengthen social health education and develop and implement stronger public policies, such as building more public sports venues [29]. We projected that the incidence of RCC will continue to increase over the next 25 years for most age groups; therefore, these strategies should be applied to people of all ages.\u003c/p\u003e\n\u003cp\u003eWe found that the increasing incidence was predominantly for localized disease, with decreasing incidence in both regional stage and distant disease. Since 1992, the proportion of localized disease has increased substantially. Localized disease currently accounts for almost two-thirds of RCC cases. In contrast, the proportions of distant and unstaged disease both decreased by half from 1992 to 2019. This is obviously attributed to the more widespread application and advances in early diagnostic measures such as abdominal imaging and examinations [30-31], which allow more incidental detection and early diagnosis of small cancerous lesions [32-33]. Early diagnosis allows potential distant RCC patients to be diagnosed at an early stage and prevents stage migration for RCC. Secondary prevention (early detection and early diagnosis) and early treatment together can prolong the survival of RCC patients and improve their long-term quality of life. To achieve comprehensive secondary prevention, the main approach is to conduct disease screening [34]. For individuals, regular health checkups might help. Public health authorities should develop relevant policies, such as providing more available health management and even free regular health checkups for people over 65 years of age with a high prevalence of RCC.\u003c/p\u003e\n\u003cp\u003eIn the 1990s, distant RCC patients were treated with interferon-\u0026alpha; (IFN-\u0026alpha;) and interleukin-2 (IL-2) alone or in combination, with poor patient survival. The results of two prospective trials, EORTC 30947 and SWOG 8949, showed that IFN-\u0026alpha; combined with nephrectomy significantly improved overall survival (OS) in advanced RCC, which established the use of nephrectomy for patients with advanced RCC [35-37]. The decrease in the IBM of distant RCC from 1998 to 2004 was associated with the introduction of this therapy. In the period analysis of IBM, the mortality risk for RCC began to decrease from 1999-2003, further illustrating that this treatment combination can reduce the risk of death from RCC. Our data also showed that the IBM among distant RCC patients started decreasing significantly in 2015. In 2015, the first immune checkpoint inhibitor (ICI), nivolumab, was used to treat RCC [38]. Subsequently, ICI-based immune combination therapies such as avelumab combined with axitinib, pembrolizumab combined with axitinib, and nivolumab combined with ipilimumab have shown significant clinical efficacy [39-41]. Immunotherapy has ushered in a new era in the treatment of RCC and improved the clinical outcomes of patients with advanced RCC [42]. Ongoing trials of combination therapy have provided potential for durable clinical benefit in the survival of RCC patients. For example, a recent trial (COSMIC-313) showed superior efficacy of the triple combination of cabozantinib, nivolumab, and ipilimumab in patients with metastatic RCC [43].\u003c/p\u003e\n\u003cp\u003eHowever, the SEER database lacks information on RCC risk factors, such as lifestyle factors, environmental exposures, and viral infection status, so we could not directly explain the direct association between individual exposure factors and RCC incidence. Thus, the association could only be inferred indirectly by investigating the trend of RCC risk factors. In addition, a large number of cases were described with unknown histology in SEER; thus, the incidence and IBM trends could not be reliably analyzed by histological subtype in this study. Nevertheless, the SEER database collects cancer diagnosis, treatment, and survival data for approximately 30% of the U.S. population, and population-based cancer registry reporting is considered the gold standard for reporting cancer rates in specific populations. Although descriptive studies cannot provide absolute evidence of causality, the findings of this study can help inform the prevention of RCC to guide the rational allocation of health resources and the targeted development of preventive intervention strategies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTreatment advances have remarkably improved the survival and moderately reduced the mortality of RCC in the US at the population level. However, the overall incidence of RCC in the US is still increasing, likely due to the rising prevalence of obesity in the US population. We projected that over the next 25 years, the incidence of RCC in the US will continue to increase if no further strengthened strategies are taken. To significantly decrease the disease burden, effective approaches to control modifiable RCC risk factors such as obesity, hypertension and smoking must be further developed and implemented immediately.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAAPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eaverage annual percent change\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eannual percent change\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal Burden of Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eincidence-based mortality\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eimmune checkpoint inhibitor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIFN-α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterferon-α\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterleukin-2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Cancer Institute\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erenal cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erate ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEER\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSurveillance, Epidemiology and End Results\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited States.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (No. 81773555).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank the National Cancer Institute and the SEER staff for providing this invaluable database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Z.F. Data curation: R.C and W.L. Formal analysis: W.L. Funding acquisition: Z.F. Investigation: S.L. H.D. and T.J. Methodology: J.H. Project administration: T.T. Resources: S.L. and W.L. Software: H.D. and T.J. Supervision: T.T. Validation: J.H. Visualization: R.C. and Si Li. Roles/Writing \u0026ndash; original draft: R.C. Writing \u0026ndash; review \u0026amp; editing: Z.F. and R.C. The work reported in the paper has been performed by the authors, unless clearly specified in the text.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient consents were not required because the study is a retrospective database research in nature, there was no direct patient contact. Institutional Review Board approval was not required according to our institution policy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are openly available in the Surveillance, Epidemiology, and End Results at \u003cem\u003ehttps://seer.cancer.gov\u003c/em\u003e [18].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. \u003cem\u003eCA Cancer J Clin\u003c/em\u003e. Jan 2023;73(1):17-48. doi:10.3322/caac.21763\u003c/li\u003e\n\u003cli\u003eHsieh JJ, Purdue MP, Signoretti S, et al. Renal cell carcinoma. \u003cem\u003eNat Rev Dis Primers\u003c/em\u003e. Mar 9 2017;3:17009. doi:10.1038/nrdp.2017.9\u003c/li\u003e\n\u003cli\u003eZnaor A, Lortet-Tieulent J, Laversanne M, Jemal A, Bray F. 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Jan 2023;41(1):101-106. doi:10.1080/07357907.2022.2136681\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cancer-causes-and-control","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caco","sideBox":"Learn more about [Cancer Causes \u0026 Control](https://www.springer.com/journal/10552)","snPcode":"10552","submissionUrl":"https://submission.nature.com/new-submission/10552/3","title":"Cancer Causes \u0026 Control","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Kidney cancer, Trends, Incidence-based mortality (IBM), Surveillance, Epidemiology and End Results (SEER), age-period-cohort analysis","lastPublishedDoi":"10.21203/rs.3.rs-4113494/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4113494/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eSignificant advances in the management, in particular the treatment, of renal cell carcinoma (RCC) has have been made over the years. However, it is not clear whether these advances reduce the disease burden of RCC at the population level.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing data from the Surveillance, Epidemiology, and End Results database, we estimated the temporal trends of RCC incidence, incidence-based mortality (IBM), and survival rates in the United States (US) from 1992 to through 2019.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom 2008 to 2019, the incidence increased slowly at 1.1% annually (95% CI: 0.6\u0026ndash;1.5%). The overall IBM rate of RCC increased by 6.8% per year (95% CI: -1.1\u0026ndash;15.3%) between 1994 and 1997, plateaued between 1997 and 2015, and then decreased nonsignificantly after 2015. During the study period, the overall 5-year survival rate of RCC continuously increased from 53.69% in 1992 to 72.90% in 2014, with the best improvement observed for RCC patients with distant disease. However, we projected that, given the current trends, the incidence of RCC in the US will continue to increase from 6.92 per 100,000 in 2015\u0026ndash;2019 to 9.59 per 100,000 in 2040\u0026ndash;2044.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOver the years, the mortality of RCC has been decreased reducing at the US populational level mainly because the considerably significantly improved survival of RCC patients at all stages through the advances in treatment. However, the overall incidence of RCC is continuously increasing, indicating that more effective preventive strategies should be developed to reduce the disease burden of RCC.\u003c/p\u003e","manuscriptTitle":"Temporal trends of the disease burden of renal cell carcinoma from 1992 to 2019 in the US: A population-based analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 16:01:36","doi":"10.21203/rs.3.rs-4113494/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-12T20:57:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-09T04:50:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247488491842605674968201133707091967220","date":"2024-11-28T02:52:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-27T13:01:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-17T13:30:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-17T13:30:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cancer Causes \u0026 Control","date":"2024-03-16T14:00:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cancer-causes-and-control","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caco","sideBox":"Learn more about [Cancer Causes \u0026 Control](https://www.springer.com/journal/10552)","snPcode":"10552","submissionUrl":"https://submission.nature.com/new-submission/10552/3","title":"Cancer Causes \u0026 Control","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"15a386cb-24f3-4afb-b414-c716aae6ca06","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-19T16:00:51+00:00","versionOfRecord":{"articleIdentity":"rs-4113494","link":"https://doi.org/10.1007/s10552-025-02007-1","journal":{"identity":"cancer-causes-and-control","isVorOnly":false,"title":"Cancer Causes \u0026 Control"},"publishedOn":"2025-05-13 15:57:34","publishedOnDateReadable":"May 13th, 2025"},"versionCreatedAt":"2024-03-21 16:01:36","video":"","vorDoi":"10.1007/s10552-025-02007-1","vorDoiUrl":"https://doi.org/10.1007/s10552-025-02007-1","workflowStages":[]},"version":"v1","identity":"rs-4113494","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4113494","identity":"rs-4113494","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}