A Nomogram to Predict Distant Metastases After Multimodality Therapy for Patients With Localized Esophageal Cancer

Restricted access

Background: Among patients with localized esophageal cancer (LEC), 35% or more develop distant metastases (DM) as first relapse, most in the first 24 months after local therapy. Implementation of novel strategies may be possible if DM can be predicted reliably. We hypothesized that clinical variables could help generate a DM nomogram. Patients and Methods: Patients with LEC who completed multimodality therapy were analyzed. Various statistical methods were used, including multivariate analysis to generate a nomogram. A concordance index (c-index) was established and validated using the bootstrap method. Results: Among 629 patients analyzed (356 trimodality/273 bimodality), 36% patients developed DM as first relapse. The median overall survival from DM was only 8.6 months (95% CI, 7.0–10.2). In a multivariate analysis, the variables associated with a higher risk for developing DM were poorly differentiated histology (hazard ratio [HR], 1.76; P<.0001), baseline T3/T4 primary (HR, 3.07; P=.0006), and baseline N+ LEC (HR, 2.01; P<.0001). Although variables associated with a lower risk for DM were age of 60 years or older (HR, 0.75; P=.04), squamous cell carcinoma (HR, 0.54; P=.013), and trimodality therapy (HR, 0.58; P=.0001), the bias-corrected c-index was 0.67 after 250 bootstrap resamples. Conclusions: Our nomogram identified patients with LEC who developed DM with a high probability. The model needs to be refined (tumor and blood biomarkers) and validated. This type of model will allow implementation of novel strategies in patients with LEC.

Current affiliations: Department of Gastrointestinal Medical Oncology, National Cancer Center Hospital, Tokyo, Japan; and Advanced Clinical Research of Cancer, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Correspondence: Jaffer A. Ajani, MD, Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 0426, Houston, TX 77054. E-mail: jajani@mdanderson.org
  • 1.

    TaketaTSudoKCorreaAM. Post chemoradiation surgical pathology stage can customize the surveillance strategy in patients with esophageal adenocarcinoma. J Natl Compr Canc Netw2014;12:11391144.

    • Search Google Scholar
    • Export Citation
  • 2.

    SiegelRNaishadhamDJemalA. Cancer statistics, 2012. CA Cancer J Clin2012;62:1029.

  • 3.

    JemalABrayFCenterMM. Global cancer statistics. CA Cancer J Clin2011;61:6990.

  • 4.

    AllumWHStenningSPBancewiczJ. Long-term results of a randomized trial of surgery with or without preoperative chemotherapy in esophageal cancer. J Clin Oncol2009;27:50625067.

    • Search Google Scholar
    • Export Citation
  • 5.

    van HagenPHulshofMCvan LanschotJJ. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med2012;366:20742084.

    • Search Google Scholar
    • Export Citation
  • 6.

    AjaniJABarthelJSBentremDJ. Esophageal and esophagogastric junction cancers. J Natl Compr Canc Netw2011;9:830887.

  • 7.

    CooperJSGuoMDHerskovicA. Chemoradiotherapy of locally advanced esophageal cancer: long-term follow-up of a prospective randomized trial (RTOG 85-01). Radiation Therapy Oncology Group. JAMA1999;281:16231627.

    • Search Google Scholar
    • Export Citation
  • 8.

    ShiozakiHSudoKXiaoL. Distribution and timing of distant metastasis after local therapy in a large cohort of patients with esophageal and esophagogastric junction cancer. Oncology2014;86:336339.

    • Search Google Scholar
    • Export Citation
  • 9.

    ShariatSFKarakiewiczPISuardiN. Comparison of nomograms with other methods for predicting outcomes in prostate cancer: a critical analysis of the literature. Clin Cancer Res2008;14:44004407.

    • Search Google Scholar
    • Export Citation
  • 10.

    GreeneFLPageDLFlemingID eds. AJCC Cancer Staging Manual. 6th ed.New York, NY: Springer-Verlag; 2002.

  • 11.

    AjaniJAXiaoLRothJA. A phase II randomized trial of induction chemotherapy versus no induction chemotherapy followed by preoperative chemoradiation in patients with esophageal cancer. Ann Oncol2013;24:28442849.

    • Search Google Scholar
    • Export Citation
  • 12.

    SudoKTaketaTCorreaAM. Locoregional failure rate after preoperative chemoradiation of esophageal adenocarcinoma and the outcomes of salvage strategies. J Clin Oncol2013;31:43064310.

    • Search Google Scholar
    • Export Citation
  • 13.

    GrambschPTherneauT. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika1994;81:515526.

  • 14.

    HarrellFEJrLeeKLMarkDB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med1996;15:361387.

    • Search Google Scholar
    • Export Citation
  • 15.

    HarrellFE. Regression modeling strategies: with applications to linear models logistic regression and survival analysis. New York, NY: Springer; 2001.

    • Search Google Scholar
    • Export Citation
  • 16.

    RohatgiPRSwisherSGCorreaAM. Failure patterns correlate with the proportion of residual carcinoma after preoperative chemoradiotherapy for carcinoma of the esophagus. Cancer2005;104:13491355.

    • Search Google Scholar
    • Export Citation
  • 17.

    PatnanaSVMurthySBXiaoL. Critical role of surgery in patients with gastroesophageal carcinoma with a poor prognosis after chemoradiation as defined by positron emission tomography. Cancer2010;116:44874494.

    • Search Google Scholar
    • Export Citation
  • 18.

    MurphyCCCorreaAMAjaniJA. Surgery is an essential component of multimodality therapy for patients with locally advanced esophageal adenocarcinoma. J Gastrointest Surg2013;17:13591369.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 66 66 9
PDF Downloads 22 22 4
EPUB Downloads 0 0 0