Skip to main content

Patients with Adenocarcinoma of the Small Intestine with 9 or More Regional Lymph Nodes Retrieved Have a Higher Rate of Positive Lymph Nodes and Improved Survival

Abstract

Purpose

To assess the influence of regional lymph node (RLN) retrieval on stage migration of adenocarcinoma of the small intestine and survival.

Patients and Methods

From the Surveillance, Epidemiology, and End Results database,1090 patients with nonmetastatic small bowel adenocarcinoma were identified in between 2004 and 2011. The impact of the number of RLNs removed on histopathological staging and oncological outcome was assessed utilizing Cox proportional hazard regression models with and without risk-adjustment, propensity score methods, and joinpoint regression analysis.

Results

The rate of node-positive cancer increased steadily with the number of retrieved RLNs up to 9 RLNs, which suggests that a minimum of 9 (95 % CI 5.5–10.5) retrieved RLNs are needed for the detection of node-positive disease (P < 0.001). From 657 of 1090 patients (60.3 %), 9 or more RLNs were retrieved. While in 2004 only in 46.0 % of all cases 9+ RLNs were retrieved, this rate increased to 69.3 % in 2011 (P < 0.001). The multivariable analysis demonstrated that the retrieval of 9+ RLNs was associated with better overall (hazard ratio of death [HR] = 0.67, 95 % CI 0.55–0.82, P < 0.001) and cancer-specific survival (HR = 0.77, 95 % CI 0.61–0.96, P = 0.022). This finding was confirmed by a propensity score-adjusted analysis, which indicated increased overall (HR = 0.67, 95 % CI 0.50–0.89, P < 0.001) and cancer-specific survival (HR = 0.67, 95 % CI 0.49–0.92, P = 0.013) in patients with the retrieval of 9+ RLNs.

Conclusion

To our knowledge, this is the first population-based propensity score-adjusted investigation in small bowel adenocarcinoma. A sufficient number of RLNs should be retrieved to achieve an optimal oncological outcome.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin 2015;65:5–29. doi:10.3322/caac.21254.

    Article  PubMed  Google Scholar 

  2. DeSesso JM, Jacobson CF. Anatomical and physiological parameters affecting gastrointestinal absorption in humans and rats. Food Chem Toxicol 2001;39:209–28.

    Article  CAS  PubMed  Google Scholar 

  3. Bilimoria KY, Bentrem DJ, Wayne JD, Ko CY, Bennett CL, Talamonti MS. Small bowel cancer in the United States: changes in epidemiology, treatment, and survival over the last 20 years. Ann Surg 2009;249:63–71. doi:10.1097/SLA.0b013e31818e4641.

    Article  PubMed  Google Scholar 

  4. Hatzaras I, Palesty JA, Abir F, Sullivan P, Kozol RA, Dudrick SJ, et al. Small-bowel tumors: epidemiologic and clinical characteristics of 1260 cases from the Connecticut tumor registry. Arch Surg 1960 2007;142:229–35. doi:10.1001/archsurg.142.3.229.

  5. Weiss NS, Yang CP. Incidence of histologic types of cancer of the small intestine. J Natl Cancer Inst 1987;78:653–6.

    CAS  PubMed  Google Scholar 

  6. Dabaja BS, Suki D, Pro B, Bonnen M, Ajani J. Adenocarcinoma of the small bowel: presentation, prognostic factors, and outcome of 217 patients. Cancer 2004;101:518–26. doi:10.1002/cncr.20404.

    Article  PubMed  Google Scholar 

  7. Bakaeen FG, Murr MM, Sarr MG, Thompson GB, Farnell MB, Nagorney DM, et al. What prognostic factors are important in duodenal adenocarcinoma? Arch Surg 1960 2000;135:635–41; discussion 641–2.

  8. Brücher BL, Stein HJ, Roder JD, Busch R, Fink U, Werner M, et al. New aspects of prognostic factors in adenocarcinomas of the small bowel. Hepatogastroenterology 2001;48:727–32.

    PubMed  Google Scholar 

  9. Wu T-J, Yeh C-N, Chao T-C, Jan Y-Y, Chen M-F. Prognostic factors of primary small bowel adenocarcinoma: univariate and multivariate analysis. World J Surg 2006;30:391–8; doi:10.1007/s00268-005-7898-6.

    Article  PubMed  Google Scholar 

  10. Overman MJ, Hu C-Y, Wolff RA, Chang GJ. Prognostic value of lymph node evaluation in small bowel adenocarcinoma: analysis of the Surveillance, Epidemiology, and End Results database. Cancer 2010;116:5374–82. doi:10.1002/cncr.25324.

    Article  PubMed  Google Scholar 

  11. Le Voyer TE, Sigurdson ER, Hanlon AL, Mayer RJ, Macdonald JS, Catalano PJ, et al. Colon cancer survival is associated with increasing number of lymph nodes analyzed: a secondary survey of intergroup trial INT-0089. J Clin Oncol 2003;21:2912–9. doi:10.1200/JCO.2003.05.062.

    Article  PubMed  Google Scholar 

  12. Smith DD, Schwarz RR, Schwarz RE. Impact of total lymph node count on staging and survival after gastrectomy for gastric cancer: data from a large US-population database. J Clin Oncol 2005;23:7114–24. doi:10.1200/JCO.2005.14.621.

    Article  PubMed  Google Scholar 

  13. Hellan M, Sun C-L, Artinyan A, Mojica-Manosa P, Bhatia S, Ellenhorn JDI, et al. The impact of lymph node number on survival in patients with lymph node-negative pancreatic cancer. Pancreas 2008;37:19–24. doi:10.1097/MPA.0b013e31816074c9.

    Article  PubMed  Google Scholar 

  14. Compton CC, Fielding LP, Burgart LJ, Conley B, Cooper HS, Hamilton SR, et al. Prognostic factors in colorectal cancer. College of American Pathologists Consensus Statement 1999. Arch Pathol Lab Med 2000;124:979–94. doi:10.1043/0003-9985(2000)124<0979:PFICC>2.0.CO;2.

    CAS  PubMed  Google Scholar 

  15. Nelson H, Petrelli N, Carlin A, Couture J, Fleshman J, Guillem J, et al. Guidelines 2000 for colon and rectal cancer surgery. J Natl Cancer Inst 2001;93:583–96.

    Article  CAS  PubMed  Google Scholar 

  16. Otchy D, Hyman NH, Simmang C, Anthony T, Buie WD, Cataldo P, et al. Practice parameters for colon cancer. Dis Colon Rectum 2004;47:1269–84.

    Article  PubMed  Google Scholar 

  17. Brenner H, Kloor M, Pox CP. Colorectal cancer. Lancet 2014;383:1490–502. doi:10.1016/S0140-6736(13)61649-9.

    Article  PubMed  Google Scholar 

  18. Harris E, Barry M, Kell MR. Supporting trials for primary tumor resection in stage IV breast cancer is paramount. Ann Surg Oncol 2013;20:3151–2. doi:10.1245/s10434-013-3098-z.

    Article  PubMed  Google Scholar 

  19. Wingo PA, Jamison PM, Hiatt RA, Weir HK, Gargiullo PM, Hutton M, et al. Building the infrastructure for nationwide cancer surveillance and control—a comparison between the National Program of Cancer Registries (NPCR) and the Surveillance, Epidemiology, and End Results (SEER) Program (United States). Cancer Causes Control CCC 2003;14:175–93.

    Article  PubMed  Google Scholar 

  20. Fritz A, Percy C, Jack A, et al. International Classification of Disease for Oncology (ed 3), Geneva, Switzerland, World Health Organization, 2000.

    Google Scholar 

  21. Davies RB. Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 1987;74:33–43.

    Google Scholar 

  22. Muggeo VMR. Estimating regression models with unknown break-points. Stat Med 2003;22:3055–71. doi:10.1002/sim.1545.

    Article  PubMed  Google Scholar 

  23. Cleveland WS, Devlin SJ. Locally-Weighted Regression: An Approach to Regression Analysis by Local Fitting. J Am Stat Assoc 1988;83 596–610.

  24. Feinstein AR, Sosin DM, Wells CK. The Will Rogers phenomenon. Stage migration and new diagnostic techniques as a source of misleading statistics for survival in cancer. N Engl J Med 1985;312:1604–8. doi:10.1056/NEJM198506203122504.

    Article  CAS  PubMed  Google Scholar 

  25. Grambsch PM, Therneau TM. Proportional Hazards Tests and Diagnostics Based on Weighted Residuals. Biometrika 1994;81:515–26. doi:10.2307/2337123.

  26. Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med 1997;127:757–63.

    Article  CAS  PubMed  Google Scholar 

  27. Joffe MM, Rosenbaum PR. Invited commentary: propensity scores. Am J Epidemiol 1999;150:327–33.

    Article  CAS  PubMed  Google Scholar 

  28. Rosenbaum PR. Model-based direct adjustment. J Am Stat Assoc 1987;82:387–94. doi:10.1080/01621459.1987.10478441.

    Article  Google Scholar 

  29. Ho DE, Imai K, King G, Stuart EA (2011) MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Soft 2011; 42(i08). doi: 10.18637/jss.v042.i08

  30. Hansen BB, Klopfer SO. Optimal full matching and related designs via network flows. J Comput Graph Stat 2006; 15:609–27. Doi: 10.1198/106186006X137047

    Article  Google Scholar 

  31. Parsons HM, Begun JW, Kuntz KM, Tuttle TM, McGovern PM, Virnig BA. Lymph node evaluation for colon cancer in an era of quality guidelines: who improves? J Oncol Pract 2013;9:e164–71. doi:10.1200/JOP.2012.000812.

    PubMed Central  Article  PubMed  Google Scholar 

  32. Dudeja V, Habermann EB, Abraham A, Zhong W, Parsons HM, Tseng JF, et al. Is there a role for surgery with adequate nodal evaluation alone in gastric adenocarcinoma? J Gastrointest Surg 2012;16:238–46; doi:10.1007/s11605-011-1756-7.

    Article  PubMed  Google Scholar 

  33. Baxter NN, Tuttle TM. Inadequacy of lymph node staging in gastric cancer patients: a population-based study. Ann Surg Oncol 2005;12:981–7. doi:10.1245/ASO.2005.03.008.

    Article  PubMed  Google Scholar 

  34. Morgan JW, Ji L, Friedman G, Senthil M, Dyke C, Lum SS. The role of the cancer center when using lymph node count as a quality measure for gastric cancer surgery. JAMA Surg 2015;150:37–43. doi:10.1001/jamasurg.2014.678.

    Article  PubMed  Google Scholar 

  35. Harmon JW, Tang DG, Gordon TA, Bowman HM, Choti MA, Kaufman HS, et al. Hospital volume can serve as a surrogate for surgeon volume for achieving excellent outcomes in colorectal resection. Ann Surg 1999;230:404–11.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  36. Miller EA, Woosley J, Martin CF, Sandler RS. Hospital-to-hospital variation in lymph node detection after colorectal resection. Cancer 2004;101:1065–71. doi:10.1002/cncr.20478.

    Article  PubMed  Google Scholar 

  37. Baiocchi GL, Tiberio GA, Minicozzi AM, Morgagni P, Marrelli D, Bruno L, et al. A multicentric Western analysis of prognostic factors in advanced, node-negative gastric cancer patients. Ann Surg 2010;252:70–3. doi:10.1097/SLA.0b013e3181e4585e.

    Article  PubMed  Google Scholar 

  38. Koo DH, Yun S-C, Hong YS, Ryu M-H, Lee J-L, Chang H-M, et al. Systemic chemotherapy for treatment of advanced small bowel adenocarcinoma with prognostic factor analysis: retrospective study. BMC Cancer 2011;11:205. doi:10.1186/1471-2407-11-205.

    PubMed Central  Article  PubMed  Google Scholar 

  39. Tsushima T, Taguri M, Honma Y, Takahashi H, Ueda S, Nishina T, et al. Multicenter retrospective study of 132 patients with unresectable small bowel adenocarcinoma treated with chemotherapy. The Oncologist 2012;17:1163–70. doi:10.1634/theoncologist.2012-0079.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  40. Zaanan A, Costes L, Gauthier M, Malka D, Locher C, Mitry E, et al. Chemotherapy of advanced small-bowel adenocarcinoma: a multicenter AGEO study. Ann Oncol 2010;21:1786–93. doi:10.1093/annonc/mdq038.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Alexander Wilhelm.

Ethics declarations

Source of Financial Support

None

Conflict of Interest

The authors declare that they have no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wilhelm, A., Müller, S.A., Steffen, T. et al. Patients with Adenocarcinoma of the Small Intestine with 9 or More Regional Lymph Nodes Retrieved Have a Higher Rate of Positive Lymph Nodes and Improved Survival. J Gastrointest Surg 20, 401–410 (2016). https://doi.org/10.1007/s11605-015-2994-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11605-015-2994-x

Keywords

  • Small intestine
  • Survival
  • Lymph nodes
  • Adenocarcinoma