Ann Surg Treat Res.  2018 Oct;95(4):183-191. 10.4174/astr.2018.95.4.183.

Prognostic influence of 3-dimensional tumor volume on breast cancer compared to conventional 1-dimensional tumor size

Affiliations
  • 1Department of Surgery, Seoul Metropolitan Government - Seoul National University Boramae Medical Center, Seoul, Korea. kiterius@snu.ac.kr
  • 2Department of Surgery, Seoul National University College of Medicine, Seoul, Korea.
  • 3Gangdong Seoul Surgical Clinic, Seoul, Korea.
  • 4Hongseong Medical Center, Hongseong, Korea.
  • 5Department of Pathology, Seoul Metropolitan Government - Seoul National University Boramae Medical Center, Seoul, Korea.

Abstract

PURPOSE
The prognostic influence of 3-dimensional tumor volume (Tv) on breast cancer compared to conventional 1-dimensional tumor size (T) was investigated.
METHODS
Analysis was performed on a cohort of 8,996 primary breast cancer patients who were initially diagnosed with TNM stage I-III. Tumor size was defined as the maximum tumor dimension, and Tv was calculated by the equation of (4π× r1 × r2 × r3)/3; r1, r2, and r3 were defined as half of the largest, intermediate, and shortest dimension of the tumor, respectively. Tv was classified into Tv1, Tv2, and Tv3 according to the cut off values of 2.056 cm3 and 20.733 cm3.
RESULTS
The survival curves according to both the T and Tv categories were clearly differentiated (all P < 0.001), as were those for staging by T and Tv (all P < 0.001). In T1 and T2 tumors, the Tv1 group showed superior survival over the Tv2 group (T1, P < 0.001; T2, P = 0.001). Univariate and multivariate analysis both indicated that Tv was a significant prognostic factor (both P < 0.001). The receiver operating characteristic curve showed that the area under the curves were 0.712 (P < 0.001) for Tv and 0.699 (P < 0.001) for T. Positive correlations were observed between the number of positive nodes and T (coefficient = 0.325; P < 0.001), and between the number of positive nodes and Tv (coefficient = 0.321; P < 0.001).
CONCLUSION
Tv classification works well for predicting the prognosis of breast cancer, and it is a better predictor than conventional T classification in several aspects. Further studies are needed to validate the practical usefulness of Tv classification in clinical settings.

Keyword

Breast neoplasms; Prognosis; Survival analysis; Tumor burden

MeSH Terms

Breast Neoplasms*
Breast*
Classification
Cohort Studies
Humans
Multivariate Analysis
Prognosis
ROC Curve
Survival Analysis
Tumor Burden*

Figure

  • Fig. 1 Overall survival curves according to T category (A), Tv category (B), Stage by T (C), and Stage by Tv (D). Tv, tumor volume.

  • Fig. 2 Overall survival curves according to the combination of T and Tv category (A), and the survival curves for the T2 & Tv1 group and the T1 & Tv2 group (B). Tv, tumor volume. *No statistical significance between the 2 survival curves.

  • Fig. 3 Overall survival curves for Tv1 and Tv2 in T1 tumors (A) and T2 tumors (B), ant the survival curves for T1 and T2 in Tv1 tumors (C) and Tv2 tumors (D). Tv, tumor volume.


Reference

1. Amin MB, Edge SB, Greene FL, Compton CC, Gershenwald JE, Brookland RK, et al. AJCC cancer staging manual. 8th ed. New York: Springer;2017.
2. American Joint Committee for Cancer Staging and End Results Reporting. Manual for staging of cancer. Chicago (IL): American Joint Committee;1977.
3. Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, et al. The Eighth Edition AJCC Cancer Staging Manual: continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging. CA Cancer J Clin. 2017; 67:93–99.
Article
4. Bhooshan N, Sharma NK, Badiyan S, Kaiser A, Moeslein FM, Kwok Y, et al. Pretreatment tumor volume as a prognostic factor in metastatic colorectal cancer treated with selective internal radiation to the liver using yttrium-90 resin microspheres. J Gastrointest Oncol. 2016; 7:931–937.
Article
5. Chen Y, Zhang Z, Jiang G, Zhao K. Gross tumor volume is the prognostic factor for squamous cell esophageal cancer patients treated with definitive radiotherapy. J Thorac Dis. 2016; 8:1155–1161.
Article
6. Timmermans AJ, Lange CA, de Bois JA, van Werkhoven E, Hamming-Vrieze O, Hilgers FJ, et al. Tumor volume as a prognostic factor for local control and overall survival in advanced larynx cancer. Laryngoscope. 2016; 126:E60–E67.
Article
7. Li MX, Zhao H, Bi XY, Li ZY, Huang Z, Han Y, et al. Total tumor volume predicts survival following liver resection in patients with hepatocellular carcinoma. Tumour Biol. 2016; 37:9301–9310.
Article
8. Hwang S, Song GW, Lee YJ, Kim KH, Ahn CS, Moon DB, et al. Multiplication of tumor volume by two tumor markers is a post-resection prognostic predictor for solitary hepatocellular carcinoma. J Gastrointest Surg. 2016; 20:1807–1820.
Article
9. Su XD, Xie HJ, Liu QW, Mo YX, Long H, Rong TH. The prognostic impact of tumor volume on stage I non-small cell lung cancer. Lung Cancer. 2017; 104:91–97.
Article
10. Jorns J, Thiel DD, Lohse CM, Williams A, Arnold ML, Cheville JC, et al. Three-dimensional tumour volume and cancer-specific survival for patients undergoing nephrectomy to treat pT1 clear-cell renal cell carcinoma. BJU Int. 2012; 110:956–960.
Article
11. Jiang N, Deng JY, Ding XW, Liu Y, Liang H. Tumor volume as a prognostic factor was superior to the seventh edition of the pT classification in resectable gastric cancer. Eur J Surg Oncol. 2015; 41:315–322.
12. Liu Z, Gao P, Liu S, Zheng G, Yang J, Sun L, et al. Tumor volume increases the predictive accuracy of prognosis for gastric cancer: a retrospective cohort study of 3409 patients. Oncotarget. 2017; 8:18968–18978.
Article
13. Voss B, Wilop S, Jonas S, El-Komy MH, Schaller J, von Felbert V, et al. Tumor volume as a prognostic factor in resectable malignant melanoma. Dermatology. 2014; 228:66–70.
Article
14. Lim ST, Jeon YW, Suh YJ. The prognostic values of preoperative tumor volume and tumor diameter in T1N0 papillary thyroid cancer. Cancer Res Treat. 2017; 49:890–897.
Article
15. Taran SJ, Taran R, Batra M, Ladia DD, Bhandari V. Survival with concurrent temozolomide and radiotherapy in pediatric brainstem glioma with relation to the tumor volume. J Pediatr Neurosci. 2015; 10:341–345.
Article
16. Lin CS, de Oliveira Santos AB, Silva EL, de Matos LL, Moyses RA, Kulcsar MA, et al. Tumor volume as an independent predictive factor of worse survival in patients with oral cavity squamous cell carcinoma. Head Neck. 2017; 39:960–964.
Article
17. Meyer CP, Hansen J, Boehm K, Tilki D, Abdollah F, Trinh QD, et al. Tumor volume improves the long-term prediction of biochemical recurrence-free survival after radical prostatectomy for localized prostate cancer with positive surgical margins. World J Urol. 2017; 35:199–206.
Article
18. Davis KS, Lim CM, Clump DA, Heron DE, Ohr JP, Kim S, et al. Tumor volume as a predictor of survival in human papillomavirus-positive oropharyngeal cancer. Head Neck. 2016; 38:Suppl 1. E1613–E1617.
Article
19. Chen MK, Chen TH, Liu JP, Chang CC, Chie WC. Better prediction of prognosis for patients with nasopharyngeal carcinoma using primary tumor volume. Cancer. 2004; 100:2160–2166.
Article
20. Atkinson EN, Brown BW, Montague ED. Tumor volume, nodal status, and metastasis in breast cancer in women. J Natl Cancer Inst. 1986; 76:171–178.
21. Partridge SC, Gibbs JE, Lu Y, Esserman LJ, Tripathy D, Wolverton DS, et al. MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival. AJR Am J Roentgenol. 2005; 184:1774–1781.
Article
22. Akazawa K, Tamaki Y, Taguchi T, Tanji Y, Miyoshi Y, Kim SJ, et al. Potential of reduction in total tumor volume measured with 3D-MRI as a prognostic factor for locally-advanced breast cancer patients treated with primary chemotherapy. Breast J. 2008; 14:523–531.
Article
23. Kim J, Yoo SW, Kang SR, Cho SG, Oh JR, Chong A, et al. Prognostic significance of metabolic tumor volume measured by (18)F-FDG PET/CT in operable primary breast cancer. Nucl Med Mol Imaging. 2012; 46:278–285.
Article
24. Jafri NF, Newitt DC, Kornak J, Esserman LJ, Joe BN, Hylton NM. Optimized breast MRI functional tumor volume as a biomarker of recurrence-free survival following neoadjuvant chemotherapy. J Magn Reson Imaging. 2014; 40:476–482.
Article
25. Newitt DC, Aliu SO, Witcomb N, Sela G, Kornak J, Esserman L, et al. Real-time measurement of functional tumor volume by MRI to assess treatment response in breast cancer neoadjuvant clinical trials: validation of the aegis SER software platform. Transl Oncol. 2014; 7:94–100.
Article
26. Son SH, Lee SW, Jeong SY, Song BI, Chae YS, Ahn BC, et al. Whole-body metabolic tumor volume, as determined by (18) F-FDG PET/CT, as a prognostic factor of outcome for patients with breast cancer who have distant metastasis. AJR Am J Roentgenol. 2015; 205:878–885.
27. Hylton NM, Gatsonis CA, Rosen MA, Lehman CD, Newitt DC, Partridge SC, et al. Neoadjuvant chemotherapy for breast cancer: functional tumor volume by MR imaging predicts recurrence-free survival-results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL. Radiology. 2016; 279:44–55.
Article
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