Time for more optimism in metastatic breast cancer?

Senkus, Elżbieta; Cardoso, Fátima; Pagani, Olivia

doi:10.1016/j.ctrv.2013.09.015

Cited by 59 publications

(54 citation statements)

References 128 publications

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“…Breast cancer spreads to a variety of organs depending on the type of breast cancer (Senkus et al, 2013). These affected sites include bone, lung, liver, brain, skin, and other organs (Weigelt et al, 2005).…”

Section: Exploring Factors Related To Metastasis Free Survival In Brementioning

confidence: 99%

“…Several studies have used different statistical methods to determine the prognostic factors of secondary breast metastasis. According to the literature, estrogen receptor (ER), progesterone receptor (PR), lymph node involvement ratio (LNR), cathepsin-D (Cath-D), tumor protein 53 (p53) , human epidermal growth factor receptor type 2 (Her2 also known as ERBB2 or HER-2/neu), tumor size, age at diagnosis, chemotherapy, and axillary nodal status at the time of diagnosis of the primary tumor are the most important prognostic factors with different impact on progression and metastases of breast cancer to various organs (Rochefort et al, 1990;Veronesi et al, 1993;Garcia et al, 1996;Inoue et al, 1998;Balleine et al, 1999;Rochefort and Liaudent-coopman, 1999;Selzner et al, 2000;Evans et al, 2004;Colleoni et al, 2005;Truong et al, 2005;Voogd et al, 2005;Weigelt et al, 2005;Palmieria et al, 2006Palmieria et al, , 2007Altundag et al, 2007;Sezgin et al, 2007;Wadasadawala et al, 2007;Gao et al, 2009;Koizumi et al, 2010;Ruiterkamp et al, 2011;Senkus et al, 2013).…”

Section: Exploring Factors Related To Metastasis Free Survival In Brementioning

confidence: 99%

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

Jafari‐Koshki

Mansourian²,

Mokarian³

2014

Asian Pacific Journal of Cancer Prevention

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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.

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Section: Exploring Factors Related To Metastasis Free Survival In Brementioning

confidence: 99%

Section: Exploring Factors Related To Metastasis Free Survival In Brementioning

confidence: 99%

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

Jafari‐Koshki

Mansourian²,

Mokarian³

2014

Asian Pacific Journal of Cancer Prevention

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“…However, these assessments are useful for the determination of the disease status at diagnosis or at treatment initiation. Breast cancer is a heterogeneous disease and its natural history exhibits significant variability (4,6). Breast cancer growth is dependent on time; however, certain cancers grow rapidly, whereas others develop slowly.…”

Section: Introductionmentioning

confidence: 99%

Implication of duration of clinical presentation on tumor progression and short-term recurrence in patients with early breast cancer

Fujii

Yajima

Morita

et al. 2015

Molecular and Clinical Oncology

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Abstract. Breast cancer growth is dependent on time and it may be of utmost importance to take into consideration the duration of clinical symptoms in order to predict which patients are at high risk for disease recurrence. The aim of this study was to determine the association between duration of clinical symptoms and disease recurrence in patients with breast cancer. A total of 139 consecutive patients with primary breast cancer who underwent a radical breast operation were retrospectively investigated and the association between recurrence and the duration of symptoms was investigated. The duration of clinical signs was defined as the time from the onset of symptoms to the date of surgery. The breast cancer cases were divided into two groups on the basis of symptom duration (≤6 and >6 months). The mean duration of symptoms was 191.0±242.6 days. Of the 139 cases, 36 (25.9%) had a duration of symptoms of >6 months. In the univariate analysis, a statistically significant association with long symptom duration was observed for disease recurrence. Of the 139 patients, 6 (4.3%) developed recurrent disease. The univariate analysis revealed that long duration of symptoms and nuclear grade were significantly associated with recurrence. In conclusion, our results indicated that breast cancer progression is dependent on time. A long duration of symptoms (>6 months) may be considered as an indicator of tumor progression and a strong prognostic factor in breast cancer patients. IntroductionAn accurate determination of poor prognostic factors for breast cancer patients may help guide the selection of more aggressive adjuvant treatment protocols. The disease stage at diagnosis is widely recognized as one of the most important prognostic factors in patients with breast cancer. Traditionally, the pathological determination of tumor size and lymph node status have guided prognosis and adjuvant therapy recommendations for patients with breast cancer (1-3). Several biomarkers, including endocrine hormone receptor status and human epidermal growth factor receptor 2 (HER2) status, have recently been added to risk evaluation and therapeutic assessment (4,5). However, these assessments are useful for the determination of the disease status at diagnosis or at treatment initiation. Breast cancer is a heterogeneous disease and its natural history exhibits significant variability (4,6). Breast cancer growth is dependent on time; however, certain cancers grow rapidly, whereas others develop slowly. The duration of symptoms is not currently incorporated into the internationally recognized staging systems. However, it may be of utmost importance to take into consideration the duration of clinical symptoms in order to identify patients at high risk for disease recurrence. The majority of patients with breast cancer are detected after the onset of symptoms, rather than through screening (7,8). The effect of the duration of the interval between symptom onset and treatment initiation on progression and survival remains uncertain and cannot be ...

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“…For some authors, optimism is a learned dimension of the personality, as a result of the interaction between inheritance -environment; other authors affirm optimism is a part of the genetic base of the personality, expressed as a dispositional feature in the middle of external situations and the individual interpretation of them (Kim & Seidlitz, 2002;Seligman, 2005). This dilemma justifies the studies to recognize if the optimism is part of an inherited structural base of the personality or a cognitive and behavioral style learned through the interaction of several psychosocial factors, as the social interaction.…”

Section: Introductionmentioning

confidence: 99%

“…Otherwise, there is a negative extremity called pessimism in opposition to the optimistic view (Salas, 2008;Seligman, 2005). The pessimistic style implies the vision of external, nonpermanent and situational causes to explain the negative events; also, a vision of internal, permanent and generalized causes to different areas of the individuals life (Remor et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

What makes us optimistic?: Psychosocial factors as predictors of dispositional optimism in young people

et al. 2014

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The present study descriptive -correlational pretended to describe the relationship between dispositional optimism, psychosocial factors such as coping, spirituality and stressful life events in parents or family caregivers and teachers and sociodemographic factors such as age, education level, family composition, gender and socioeconomic status. The sample was formed by 319 high school students (male and female), between 12 and 18 years old; 138 parents and 19 teachers. It was used the Cuestionario de Optimismo Disposicional ; the Coping Style Inventory (Archila &Londoño, 2004), Stressful Life Events Scale (WHO); the Index of Spirituality and Wellness (Daaleman & Frey, 2004). The comparative and associative multivariate analysis showed that mixed coping in young people (social support, fantasy and self-blame) in addition to mixed coping in parents (problem solving and social support) predicted dispositional optimism in young people.

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Time for more optimism in metastatic breast cancer?

Cited by 59 publications

References 128 publications

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

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

Implication of duration of clinical presentation on tumor progression and short-term recurrence in patients with early breast cancer

What makes us optimistic?: Psychosocial factors as predictors of dispositional optimism in young people

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