Browse > Article
http://dx.doi.org/10.7314/APJCP.2014.15.22.9673

Exploring Factors Related to Metastasis Free Survival in Breast Cancer Patients Using Bayesian Cure Models  

Jafari-Koshki, Tohid (Department of Biostatistics, School of Health, Sabzevar University of Medical Sciences)
Mansourian, Marjan (Department of Biostatistics and Epidemiology, Health School, Isfahan University of Medical Sciences)
Mokarian, Fariborz (Cancer Prevention Research Center, Isfahan University of Medical Sciences)
Publication Information
Asian Pacific Journal of Cancer Prevention / v.15, no.22, 2014 , pp. 9673-9678 More about this Journal
Abstract
Background: Breast cancer is a fatal disease and the most frequently diagnosed cancer in women with an increasing pattern worldwide. The burden is mostly attributed to metastatic cancers that occur in one-third of patients and the treatments are palliative. It is of great interest to determine factors affecting time from cancer diagnosis to secondary metastasis. Materials and Methods: Cure rate models assume a Poisson distribution for the number of unobservable metastatic-component cells that are completely deleted from the non-metastasis patient body but some may remain and result in metastasis. Time to metastasis is defined as a function of the number of these cells and the time for each cell to develop a detectable sign of metastasis. Covariates are introduced to the model via the rate of metastatic-component cells. We used non-mixture cure rate models with Weibull and log-logistic distributions in a Bayesian setting to assess the relationship between metastasis free survival and covariates. Results: The median of metastasis free survival was 76.9 months. Various models showed that from covariates in the study, lymph node involvement ratio and being progesterone receptor positive were significant, with an adverse and a beneficial effect on metastasis free survival, respectively. The estimated fraction of patients cured from metastasis was almost 48%. The Weibull model had a slightly better performance than log-logistic. Conclusions: Cure rate models are popular in survival studies and outperform other models under certain conditions. We explored the prognostic factors of metastatic breast cancer from a different viewpoint. In this study, metastasis sites were analyzed all together. Conducting similar studies in a larger sample of cancer patients as well as evaluating the prognostic value of covariates in metastasis to each site separately are recommended.
Keywords
Breast cancer; metastasis; survival; cure model; Bayesian;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Altundag K, Bondy ML, Mirza NQ, et al (2007). Clinicopathologic characteristics and prognostic factors in 420 metastatic breast cancer patients with central nervous system Metastasis. Cancer, 110, 2640-7.   DOI   ScienceOn
2 American Cancer Society (2011). Global cancer facts & figures 2nd edition; estimated number of new cancer cases by World Area, 2008.
3 Andre F, Slimane K, Bachelot T, et al (2004). Breast cancer with synchronous metastases: trends in survival during a 14-year period. J Clin Ontol, 22, 3302-8.   DOI   ScienceOn
4 Babu GR, Samari G, Cohen SP, et al (2011). Breast cancer screening among females in Iran and recommendations for improved practice. Asian Pac J Cancer Prev, 12, 1647-55.
5 Balleine R, Earl M, Greenberg M, et al (1999). Absence of progesterone receptor associated with secondary breast cancer in postmenopausal women. Br J Cancer, 79, 1564-71.   DOI
6 Basu S, Tiwari RC (2010). Breast cancer survival, competing risks and mixture cure model: a Bayesian analysis. J Royal Statist Soc, 173, 307-29.   DOI
7 Carter C, Allen C, Henson D (1989). Relation of tumor size, lymph node status, and survival in 24,740 breast cancer cases. Cancer, 63, 181-7.   DOI   ScienceOn
8 Chen M-H, Ibrahim JG, Sinha D (1999). A new bayesian model for survival data with a surviving fraction. J Am Statistical Association, 94, 909-19.   DOI   ScienceOn
9 Colleoni M, Rotmensz N, Peruzzotti G, et al (2005). Size of breast cancer metastases in axillary lymph nodes: clinical relevance of minimal lymph node involvement. J Clin Oncol, 23.
10 Congdon PD 2010. Applied bayesian hierarchical methods, chapman & hall/CRC.
11 Eichler AF, Kuter I, Ryan P, et al (2008). Survival in patients with brain metastases from breast cancer. Cancer, 112, 2359-67.   DOI   ScienceOn
12 Evans AJ, James JJ, Cornford EJ, et al (2004). Brain metastases from breast cancer: identification of a high-risk group. Clin Oncol, 16, 345-9.   DOI
13 Foster TS, Miller JD, Boye ME, et al (2011). The economic burden of metastatic breast cancer: a systematic review of literature from developed countries. Cancer Treat Rev, 37, 405-15.
14 Gao D, Du J, Cong L, et al (2009). Risk factors for initial lung metastasis from breast invasive ductal carcinoma in stages i-iii of operable patients. Jpn J Clin Oncol, 39, 97-104.
15 Jemal A, Bray F, Center MM, et al (2011). Global Cancer Statistics. CA Cancer J Clin, 61, 69-90.   DOI
16 Garcia M, Platet N, Liaudet E, et al (1996). Biological and clinical significance of cathepsin d in breast cancer Metastasis. Stem Cells, 14, 642-50.   DOI
17 Ibrahim JG, Chen M-H, Sinha D (2001). Bayesian survival analysis, springer-verlag New York.
18 Inoue H, Kawada A, Takasu H, et al (1998). Cathepsin D expression in skin metastasis of breast cancer. J Cutaneous Pathology, 25, 365-9.   DOI
19 Johnston SRD (2010). Living with secondary breast cancer: coping with an uncertain future with unmet needs. European J Cancer Care, 19, 561-3.   DOI
20 Koizumi M, Yoshimoto M, Kasumi F, et al (2010). An open cohort study of bone metastasis incidence following surgery in breast cancer patients. BMC Cancer, 10, 381.   DOI
21 Koscielny S, Tubiana M, Le M, et al (1984). Breast cancer: relationship between the size of the primary tumour and the probability of metastatic dissemination. Br J Cancer, 49, 709-15.   DOI   ScienceOn
22 Lamyian M, Hydarnia A, Ahmadi F, et al (2007). Barriers to and factors facilitating breast cancer screening among Iranian women: a qualitative study. East Med Health J, 13, 1160-9.
23 Largillier R, Ferrero J-M, Doyen J, et al (2008). Prognostic factors in 1038 women with metastatic breast cancer. Ann Oncol, 19, 2012-9.   DOI   ScienceOn
24 Lunn D, Spiegelhalter D, Thomas A, et al (2009). The BUGS project: Evolution, critique, and future directions. Statistics in Medicine, 28, 3049-67.   DOI   ScienceOn
25 Morris PG, Murphy CG, Mallam D, et al (2012). Limited overall survival in patients with brain metastases from triple negative breast cancer. Breast J, 1-6.
26 Mayer M, Hunis A, Oratz R, et al (2010). Living with metastatic breast cancer: a global patient survey. Community Oncology, 7, 406-12.   DOI
27 Minisini AM, Moroso S, Gerratana L, et al (2013). Risk factors and survival outcomes in patients with brain metastases from breast cancer. clinical and experimental metastasis.
28 Montazeri A, Vahdaninia M, Harirchi I, et al (2008). Breast cancer in Iran: need for greater women awareness of warning signs and effective screening methods. Asia Pac Family Medicine, 7.
29 Mousavi SM, Gouya MM, Ramazani R, et al (2009). Cancer incidence and mortality in Iran. Ann Oncol, 20, 556-63.
30 Mousavi SM, Montazeri A, Mohagheghi MA, et al (2007). Breast cancer in Iran: an epidemiological review. Breast J, 13, 383-91.   DOI   ScienceOn
31 Nieder C, Marienhagenz K, Thammx R, et al (2008). Prediction of very short survival in patients with brain metastases from breast cancer. Clin Oncol, 20, 337-9.   DOI
32 Noroozi A, Jomand T, Tahmasebi R (2011). Determinants of breast self-examination performance among iranian women: an application of the health belief model. J Canc Educ, 26, 365-74.   DOI   ScienceOn
33 Oltean D, Dicu T, Eniu D (2009). Brain metastases secondary to breast cancer: symptoms, prognosis and evolution. Tumori, 95, 697-701.
34 Othus M, Barlogie B, LeBlanc ML (2012a). Cure models as a useful statistical tool for analyzing survival. Clin Cancer Res.
35 Rochefort H, Capony F, Garcia M (1990). Cathepsin D: A protease involved in breast cancer metastasis. Cancer Metastasis Reviews, 9, 321-31.   DOI
36 Othus M, Barlogie B, LeBlanc ML, et al (2012b). Cure models as a useful statistical tool for analyzing survival. Clin Cancer Res, 18, 3731-6.   DOI
37 Palmieria D, Smithb QR, Lockmanb PR, et al (2006, 2007). Brain metastases of breast cancer. Breast Disease, 26, 139-47.
38 Rama R, Swaminathan R, Venkatesan P (2010). Cure models for estimating hospital-based breast cancer survival. Asian Pac J Cancer Prev, 11, 387-91.
39 Rochefort H, Liaudent-coopman E (1999). Cathepsin D in cancer metastasis: A protease and a ligand. APMIS, 107, 86-95.   DOI   ScienceOn
40 Ruiterkamp J, Ernst MF, de Munck L, et al (2011). Improved survival of patients with primary distant metastatic breast cancer in the period of 1995-2008. Breast Cancer Res Treat, 128, 495-503.   DOI
41 Santen G, Danhof M, Della Pasqua O (2008). Evaluation of treatment response in depression studies using a Bayesian parametric cure rate model. J Psychiatric Res, 42, 1189-97.   DOI
42 Selzner M, Morse MA, Vredenburgh JJ, et al (2000). Liver metastases from breast cancer: long-term survival after curative resection. Surgery, 127, 383-9.   DOI
43 Senkus E, Cardoso F, Pagani O (2013). Time for more optimism in metastatic breast cancer? Cancer Treatment Reviews, 40, 220-8.
44 Sezgin C, Gokmen E, Esassolak M, et al (2007). Risk factors for central nervous system metastasis in patients with metastatic breast cancer. Medical Oncology, 24, 155-61.   DOI
45 Van Der Wal Bch, Butzelaar Rmjm, Van Der Meij S, et al (2002). Axillary lymph node ratio and total number of removed lymph nodes: predictors of survival in stage I and II breast cancer. Eur J Surg Oncol, 28, 481-9.   DOI   ScienceOn
46 Sposto R (2002). Cure model analysis in cancer: an application to data from the children's cancer group. Statist Med, 21, 293-312.   DOI   ScienceOn
47 Taghavi A, Fazeli Z, Vahedi M, et al (2012). Increased trend of breast cancer mortality in Iran. Asian Pac J Cancer Prev, 13, 367-70.   과학기술학회마을   DOI   ScienceOn
48 Truong PT, Berthelet E, Lee J, et al (2005). The prognostic significance of the percentage of positive/dissected axillary lymph nodes in breast cancer recurrence and survival in patients with one to three positive axillary lymph nodes. Cancer, 103, 2006-14.   DOI   ScienceOn
49 Veronesi U, Galimberti V, Zurrida S, et al (1993). Prognostic significance of number and level of axillary node metastases in breast cancer. The Breast, 2, 224-8.   DOI
50 Voogd AC, Cranenbroek S, de Boer R, et al (2005). Long-term prognosis of patients with axillary recurrence after axillary dissection for invasive breast cancer. European Journal of Surgical Oncol, 31, 485-9.   DOI
51 Wadasadawala T, Gupta S, Bagul V, et al (2007). Brain metastases from breast cancer: Management approach. Journal of Cancer Research and Therapeutics, 3, 157-65.   DOI
52 Weigelt B, Peterse JL, van 't Veer LJ (2005). Breast Cancer Metastasis: Markers and Models. Nature Reviews, Cancer, 5, 591-602.   DOI   ScienceOn
53 Yu XQ, De Angelis R, Andersson TML, et al (2013). Estimating the proportion cured of cancer: Some practical advice for users. Cancer Epidemiology, 37, 936-842.
54 Yamasaki S, Okino T, Kan N, et al (1992). Factors influencing the response and survival of patients with liver metastases from breast cancer receiving OK-432-combined adoptive immunotherapy. J Cancer Res Clin Oncol, 118, 157-62.   DOI
55 Yin G, Ibrahim JG (2005). Cure rate models: a unified approach. Canadian J Statistics, 33, 559-70.   DOI