Skip to main content

Advertisement

SpringerLink
Log in

Patterns of surveillance intensity in kidney cancer

  • Urology - Original Paper
  • Published:
International Urology and Nephrology Aims and scope Submit manuscript

Abstract

Purpose

Surveillance guidelines for kidney cancer following surgery are heterogeneous, making it unclear what factors influence surveillance intensity in practice. Thus, we assessed the patterns of surveillance intensity in kidney cancer after primary surgery among patients ≥ 66 years.

Methods

Non-metastatic kidney cancer patients after primary surgery (n = 2433) from 2007 to 2011 were identified in SEER-Medicare. Surveillance intensity was measured as the number of unique inpatient and outpatient claims made for kidney cancer starting 60 days after primary surgery. Multivariable linear regressions assessed relationships between patient factors and surveillance intensity (log-transformed). Parameters were reported using risk ratios (RRs).

Results

Patients diagnosed in contemporary years experienced 10% more surveillance visits/12 months (RR 1.10 for every 1-year increase, 95% CI 1.07–1.13, p < 0.001). Compared to pT1 stage, patients with pT2-4 disease experienced 108% more surveillance visits/12 months (RR 2.08, 95% CI 1.90–2.27, p < 0.001). Both older age and living in a metro/urban area, as compared to a big metropolitan location, were associated with significantly fewer follow-up visits (10-year increase in age: RR 0.89, 95% CI 0.83–0.95, p < 0.001; metro/urban: RR 0.86, 95% CI 0.79–0.93, p < 0.001). Surgery type (radical, partial or ablation), gender, race and Charlson comorbidity score were not significantly associated with surveillance intensity.

Conclusions

Similar to guidelines, surveillance intensity in practice was associated with stage, but not with surgery type. Other factors such as diagnosis year, care location and patient age were associated with the amount of surveillance administered by the clinician. These additional influences are augmenting the heterogeneous delivery of kidney cancer surveillance care.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. National Comprehensive Cancer Network (NCCN). NCCN Guidelines for Treatment of Cancer by Site https://www.nccn.org/professionals/physician_gls/default.aspx#site. Accessed 15 June 2020

  2. Portnoy DB, Scott-Sheldon LA, Johnson BT, Carey MP (2008) Computer-delivered interventions for health promotion and behavioral risk reduction: a meta-analysis of 75 randomized controlled trials, 1988–2007. Prev Med 47(1):3–16

    Article  Google Scholar 

  3. Goessens BM, Visseren FL, de Nooijer J, van den Borne HW, Algra A, Wierdsma J, van der Graaf Y, SMART Study Group (2008) A pilot-study to identify the feasibility of an Internet-based coaching programme for changing the vascular risk profile of high-risk patients. Patient Educ Couns 73:67–72

    Article  Google Scholar 

  4. Kim EH, Vetter JM, Kuxhausen AN, Song JB, Sandhu GS, Strope SA (2016) Limited use of surveillance imaging following nephrectomy for renal cell carcinoma. Urol Oncol 34(237):e11-18

    Google Scholar 

  5. Feuerstein MA, Atoria CL, Pinheiro LC, Huang WC, Russo P, Elkin EB (2016) Patterns of surveillance imaging after nephrectomy in the Medicare population. BJU Int 117:280–286

    Article  Google Scholar 

  6. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383

    Article  CAS  Google Scholar 

  7. Deyo RA, Cherkin DC, Ciol MA (1992) Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45:613–619

    Article  CAS  Google Scholar 

  8. Romano PS, Roos LL, Jollis JG (1993) Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 46:1075–1079 (Discussion 81–90)

    Article  CAS  Google Scholar 

  9. Sandock DS, Seftel AD, Resnick MI (1995) A new protocol for the followup of renal cell carcinoma based on pathological stage. J Urol 154:28–31

    Article  CAS  Google Scholar 

  10. Stephenson AJ, Chetner MP, Rourke K, Gleave ME, Signaevsky M, Palmer B, Kuan J, Brock GB, Tanguay S (2004) Guidelines for the surveillance of localized renal cell carcinoma based on the patterns of relapse after nephrectomy. J Urol 172:58–62

    Article  Google Scholar 

  11. Hillman BJ, Goldsmith J (2010) Imaging: the self-referral boom and the ongoing search for effective policies to contain it. Health Aff (Millwood) 29:2231–2236

    Article  Google Scholar 

  12. DiMatteo MR, Lepper HS, Croghan TW (2000) Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch Intern Med 160:2101–2107

    Article  CAS  Google Scholar 

  13. Manning WG Jr, Wells KB (1992) The effects of psychological distress and psychological well-being on use of medical services. Med Care 30:541–553

    Article  Google Scholar 

  14. Bianchi M, Gandaglia G, Trinh QD, Hansen J, Becker A, Abdollah F, Tian Z, Lughezzani G, Roghmann F, Briganti A, Montorsi F, Karakiewicz PI, Sun M (2014) A population-based competing-risks analysis of survival after nephrectomy for renal cell carcinoma. Urol Oncol 32(46):e1-7

    Google Scholar 

  15. Kutikov A, Egleston BL, Wong YN, Uzzo RG (2010) Evaluating overall survival and competing risks of death in patients with localized renal cell carcinoma using a comprehensive nomogram. J Clin Oncol 28:311–317

    Article  Google Scholar 

  16. Stewart-Merrill SB, Thompson RH, Boorjian SA, Psutka SP, Lohse CM, Cheville JC, Leibovich BC, Frank I (2015) Oncologic surveillance after surgical resection for renal cell carcinoma: a novel risk-based approach. J Clin Oncol 33:4151–4157

    Article  Google Scholar 

  17. Motzer RJ, Hutson TE, Tomczak P, Michaelson MD, Bukowski RM, Oudard S, Negrier S, Szczylik C, Pili R, Bjarnason GA, Garcia-del-Muro X, Sosman JA, Solska E, Wilding G, Thompson JA, Kim ST, Chen I, Huang X, Figlin RA (2009) Overall survival and updated results for sunitinib compared with interferon alfa in patients with metastatic renal cell carcinoma. J Clin Oncol 27:3584–3590

    Article  CAS  Google Scholar 

  18. Stewart SB, Thompson RH, Psutka SP, Cheville JC, Lohse CM, Boorjian SA, Leibovich BC (2014) Evaluation of the National Comprehensive Cancer Network and American Urological Association Renal Cell Carcinoma surveillance guidelines. J Clin Oncol 32:4059–4065

    Article  Google Scholar 

  19. Curran V, Rourke J (2004) The role of medical education in the recruitment and retention of rural physicians. Med Teach 26:265–272

    Article  Google Scholar 

  20. Rourke J (2010) How can medical schools contribute to the education, recruitment and retention of rural physicians in their region? Bull World Health Organ 88:395–396

    Article  Google Scholar 

  21. Khuri SF, Najjar SF, Daley J, Krasnicka B, Hossain M, Henderson WG, Aust JB, Bass B, Bishop MJ, Demakis J, DePalma R, Fabri PJ, Fink A, Gibbs J, Grover F, Hammermeister K, McDonald G, Neumayer L, Roswell RH, Spencer J, Turnage RH, VA National Surgical Quality Improvement Program (2001) Comparison of surgical outcomes between teaching and nonteaching hospitals in the Department of Veterans Affairs. Ann Surg 234:370–382 (Discussion 382-383)

    Article  CAS  Google Scholar 

  22. Ayanian JZ, Weissman JS (2002) Teaching hospitals and quality of care: a review of the literature. Milbank Q 80:569–593

    Article  Google Scholar 

  23. Cahn DB, Foote C, Smaldone MC (2018) Challenges facing regionalization of radical cystectomy. Transl Androl Urol 7:292–294

    Article  Google Scholar 

Download references

Funding

None.

Author information

Authors and Affiliations

  1. Division of Urology, Department of Surgery, Penn State College of Medicine, The Pennsylvania State University, 500 University Drive, H055, Hershey, PA, 17033-0850, USA

    Suzanne B. Merrill

  2. Penn State College of Medicine, Hershey, PA, USA

    Justin Loloi

  3. Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA

    Eric W. Schaefer

  4. Department of Health Policy and Administration, The Pennsylvania State University, University Park, PA, USA

    Christopher S. Hollenbeak

Authors
  1. Suzanne B. Merrill
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Justin Loloi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eric W. Schaefer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christopher S. Hollenbeak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Suzanne B. Merrill.

Ethics declarations

Conflict of interest

All authors declare no conflicts of interest regarding this research and submission of this manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Merrill, S.B., Loloi, J., Schaefer, E.W. et al. Patterns of surveillance intensity in kidney cancer. Int Urol Nephrol 53, 447–453 (2021). https://doi.org/10.1007/s11255-020-02685-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11255-020-02685-7

Keywords

Search

Navigation