Comparisons in São Paulo and Porto Alegre were further carried out using CPMR instead of rates to estimate the number of expected deaths among Ashkenazi women in both cities. Despite the fact that CPMR are more robust indicators than proportional mortality ratios, since variation on site-specific cancer proportions according to all cancer deaths is usually shorter than according to all causes of death, lack of accuracy on these estimates cannot be dis- missed. Nevertheless, in support of such comparisons, high reliability and accuracy of reported causes of death from cancer in Brazil has been previously reported [11–13]. In the present study, we analyzed breastcancermortality among Ashkenazi women, but not incidence, and the rela- tively low overall ratios of observed versus expected deaths could just reflect a better medical care offered to this group than to the general population. Nevertheless, this seems unlikely to explain the low ratios observed among younger affected women, usually presenting an aggressive clinical evolution. On the contrary, a better disease-free survival among Ashkenazi women than in the general population also seems to be unexpected for those affected until the mid-1980s, before mammography availability in Brazil. Origin misclassification (Ashkenazi versus Sepharad) could also yield data misinterpretation, but this seems improbable since the majority of reviewed death certificates were from women born in Eastern and Central Europe.
There were concerns that screening exposure data collected from the breast screening call/recall system might not accurately reflect screening prior to 1995. Validation by checking detailed screening histories of over 100 000 individuals indicated a high level of accuracy and completeness overall, but there was evidence of some missing screening information in some areas before 1995. The effect of this would be to dilute a positive effect of screening. Temporal differences between exposure groups in our intention to screen IBM analyses mean they are potentially confounded by changes in non-screening factors over time. Falling UK breastcancermortality rates since 1990 are likely to be due to a combination of factors, including improvements in treatment and the direct effect of screening through earlier detection and treatment. In addition, there are likely to be indirect screening effects which include increased breast awareness associated with promotion of the NHSBSP (Stockton et al, 1997) and better access to multi-disciplinary breast care (Department of Health and Welsh Office, 1995; Kalager et al, 2010). Although we have identified a reduction in breastcancermortality associated with NHSBSP screening, we were not able to differentiate the contribution made by the direct and indirect effects of screening. Temporal differences between exposure groups in our intention-to-screen IBM analyses mean they are potentially confounded by changes in non-screening factors over time. However, these temporal differences were relatively small, thus minimising the likelihood of confounding due to changes in non-screening factors. Furthermore, use of Tamoxifen and adjuvant therapy was widespread during the period covered by this evaluation (Alexander et al, 1994; Moritz et al, 1997; Swerdlow and Jones, 2005) so that changes in these factors are unlikely to have substantially affected the results.
Abstract: The purpose of this study is to determine how receipt of guideline-concordant care (GCC) is associated with breastcancer-specific mortality (BCSM) and non-breastcancermortality (NBCM) among older women with breastcancer. The SEER-Medicare data was used to identify 142, 433 women age > 66 diagnosed with stage I-III breastcancer between 2007-2011. Receipt of GCC was determined according to evidence-based treatment guidelines. Cause-specific Cox proportional hazard multivariable regression models were used to estimate the association between GCC and the risk of BCSM, considering NBCM as a competing event, and NBCM, considering BCSM as a competing event, within five years of diagnosis or until end of follow-up. Among older women with breastcancer, 6.5% experienced BCSM and 11.9% experienced NBCM. GCC was associated with a 24% decreased risk of BCSM (AHR, 0.76; 95% CI, 0.71-0.82), but a 80% increased risk of NBCM (AHR, 1.80; 95% CI, 1.70-1.92). Receipt of adjuvant endocrine therapy was associated with an increased risk of BCSM and a decreased risk for NBCM. Receipt of chemotherapy was associated with an increased risk for BCSM and NBCM, while radiation therapy was associated with a decreased risk of NBCM. Women with a pre-existing dementia, arthritis, hypertension, stroke and increased comorbidity burden had an increased risk for BCSM. Most older breastcancer patients do not receive GCC, yet relatively few die from breastcancer. While GCC does decrease the risk of BCSM, the decision to treat should be made considering the patients existing health status, given that pre-existing comorbidity increases the risk for both BCSM and NBCM. Mortality differences associated with specific types of treatment may be attributed to patient selection for treatment based on worse cancer prognostic factors.
In our study, the rates of employment were more than 90% in younger groups and less than 60% in older groups. Some studies have shown the breastcancermortality in women who were employed were higher than those who never work . The retirement age for women was 50 years according to State Council on the workers retire or resign Interim Measures. Many retired women had less work stress. Some studies showed high levels of strain were associated with a slight increase in the risk of breastcancer .
The variation trends in the age-specific breastcancermortality among Chinese females aged 20–79 during 1990–2009 are shown in Fig. 1. Regardless of the time period, the breastcancermortality generally increased with age, and the breastcancermortality rates increased at a steady rate before the subjects reached 55 years old. However, breastcancermortality decreased in the group aged 60–64 years old, and then continued to increase again from 65 years old. From the change trend in the period perspective, the breastcancermortality rates of all age groups in the periods 1990–1994, 1995–1999 and 2000–2004 presented a decrease with the time period, except for 2005–2009. In particular, for the patients 50 years old and older, the breastcancermortality rates of all age groups in the time period 2005–2009 were higher than those of the other three periods.
confidence interval (95% CI) for each 5-year calendar period was estimated using Poisson regression and ad- justed for age. Relative index of inequality (RII) for breastcancermortality was used as an inequality meas- ure. To obtain RII, we ordered the educational groups from highest (tertiary) to lowest (no formal education or primary) and calculated the cumulative percentage dis- tribution of each educational group by 5-year age groups and 5-year calendar periods. Poisson regression model was used to estimate the RII. These analyses were per- formed using SAS software version 9.3 (SAS Institute, Cary, NC, USA).
patients participate in clinical trials (Sateren et al. 2002). This is scant compared to the fact that over 60 percent of children with cancer participate in cancer clinical trials. This issue has spurred numerous studies geared to identify barriers associated with cancer clinical trial enrollment. Numerous barriers to cancer clinical trial enrollment have been found, some of which include geography, racial obstacles and physician awareness (NCI 2001). Racial obstacles regarding cancer clinical trial enrollment is a major public health issue due to the disproportionate burden of the disease. In Georgia, African American males are 20 percent more likely to be diagnosed with and 39 percent more likely to die from cancer than their white counterparts. In addition, breastcancermortality rates for African American women in the state are 33 percent higher that Caucasian women. African American women in Georgia also experience colorectal cancermortality rates 71 percent higher than their white counterparts (Singh et al. 2005). Yet, African Americans have lower cancer clinical trial participation than whites (Corbie-Smith et al. 2004). It is important to ensure that clinical trial participants reflect the entire population and that cancer clinical trial results are generalizable (Etling et al. 2006).
The findings of our study suggest that breastcancer was decreasing over the time, except eastern region in 2011. One possible explanation for the role of region may be the effect of economic levels. Recently, there have been suggestions that female breastcancermortality was higher in the high economic levels than in the low economic levels . In Inner Mongolia, the western region has the highest economic levels, followed by the middle region, and eastern region is lower than these regions. Our data is in agreement with this trend. However, this trend requires further research.
Additionally, in disease-specific examinations, patients with less lymph node involvement and ER positive tumors also had less breastcancermortality. Patients who had non- randomized, clinically administered adjuvant chemotherapy had increased breastcancermortality, which is indicative of a more advanced stage. Although based on only a small number of patients (N = 74), we observed that those administered trastuzumab experienced higher cardiovascular mortality. Non-Caucasians experienced increased other type of mortality, which refines the main trial observation that race impacted overall survival . Finally, clinical administration of radiotherapy was associated with better other type mortality which likely reflects better overall health of those offered radiotherapy. This competing risks assessment was not protocol specified. The data are those from the MA.27 final analysis database, with limited relatively short median 4.1-year follow-up, which is the longest uniform follow-up possible due to trial closure. However, MA.27 is to date the largest AI alone phase III trial, so the evidence is important. Consistently, patients in our AI therapy trials (MA.17 and MA.27) experienced a substantive proportion of non- breastcancer deaths and increased non-breastcancer death with older age. The breastcancer disease attributes of tumor size and hormone receptor status were differentially associated with type of mortality, affecting breastcancer death for the MA.27 primary adjuvant trial MA.27. Previous cardiovascular disease was differentially associated with type of death, through increased unspecified other cause in MA.17 and cardiovascular death in MA.27. The introduction of trastuzumab during late accrual phase of MA.27 resulted in only 74 patients receiving this therapy, so we note with caution the increased cardiovascular mortality in conjunction with AI administration. Likewise, the observation of minority women having increased other type mortality is reported in the context that only 5 % of MA. 27’s 7576 patients were not white; in the main trial report, race had a significant predictive
Introduction: The death rates from breastcancer have declined in the past decades; however, disparities between racial/ethnic groups remain. South Carolina has some of the largest health disparities in the nation, particularly breastcancer morbidity and mortality. The Best Chance Network was established to reduce the burden of breastcancer among disadvantaged women in the state. Although much has been done to identify factors related to breastcancermortality, little has been done to examine the influence of geographic accessibility to health facilities and breastcancermortality. The purpose of this study was to investigate whether travel distance to the screening referral provider and mammography facility are associated with breastcancer-specific and all-cause mortality among women participating in South Carolina’s Best Chance Network. We also sought to contrast and compare by race breastcancer-specific and all-cause survival among BCN participants. Methods: Women in South Carolina’s Best Chance Network, who
Certain characteristics of our study may explain the dif- ferences between our results and previous work. First, the homogeneity of our sample, which included only patients with low comorbidity, could partially explain the stronger prognostic role of obesity observed in population-based studies than in our study. Such differences in effect may be attributed to other conditions such as diabetes, metabolic syndrome, and other chronic diseases that are associated both with obesity and with poorer prognoses. Because of the criteria used in clinical trials, obese patients with im- paired health due to these conditions have a lower prob- ability of being included in a clinical trial. Second, the assessment necessary to establish patient eligibility for a clinical trial may result in more accurate staging and con- sequently less confounding between obesity and delayed diagnosis often observed in obese women. Third, our re- sults are based on a large sample size of more than 5,600 patients. Pooled analyses have shown that risk estimates based on retrospective analysis of clinical trials often de- cline as the sample size increases [9-11]. Finally, all our patients were treated homogeneously with anthracycline- based CT, such an effective treatment that it may have Table 2 Multivariate Cox proportional hazards regression analysis of effect of BMI and each study variable on overall mortality, breastcancermortality, and recurrence in basic models (adjusted for study and treatment regimen only) (Continued)
Table 1 summarizes the effects of correcting for self- selection in a population where breast screening is intro- duced. As said before, women not likely to participate in screening have a higher risk of breastcancer death that is independent of the existence of screening. Thus, before screening starts, the risk of breastcancer death of women likely to participate in screening is known to be 30% to 60% lower than that of women unlikely to participate [16-18]. For our example, we opted for a relative risk of breastcancer death of 0.60, meaning that before screen- ing starts, the risk of death in participants was 40% lower than that in non-participants. The scenario in Panel A assumes no effect of screening on breastcancer mortal- ity. A case-control study after a period of screening will find a crude risk of death of 0.61 in participants versus non-participants, but the correction for self-selection will yield an adjusted relative risk of 1.00, in agreement with no screening effectiveness. In Panel B, a 20% mortality reduction is obtained thanks to screening, and the cor- rection leads to the right estimation of screening effec- tiveness. Panels C and D are similar to Panels A and B, but during the screening period, a 25% reduction change in mortality occurs that is unrelated to screening (for example, because of improved treatment). The Dr quan- tities are smaller because improved treatments have reduced the risk of breastcancer death in non-partici- pants. As a consequence, the corrected relative risk in Panel C suggests that participation in screening is asso- ciated with a 44% (that is, 100 × (1.00-0.66)) reduction in breastcancermortality, when in reality screening had no impact. The relative risk in Panel D is compatible with true screening effectiveness but the estimated mortality reduction of 52% (that is, 100 × (1.00-0.48)) is much lar- ger than the 20% reduction actually due to screening.
We used Cox regression models to compute crude and adjusted hazard ratios (HR) including 95% confi- dence intervals (95% CI) comparing the risk of recur- rence and all-cause mortality, respectively, according to thyroid status (normal thyroid versus prevalent/incident hypothyroidism) . The proportional hazard assump- tion was checked by visual inspection of the log of the estimated survivor function in the models involving prevalent hypothyroidism (Additional file 2). The models accounted for competing risks and included adjustments for potential confounding covariates including age at diagnosis (continuous), menopausal status, UICC stage, ET/ER status, surgery type, receipt of chemotherapy, histologic grade, comorbidity, and use of simvastatin or aspirin, respectively. Simvastatin and aspirin use were modelled as time-varying covariates lagged by 1 year after redemption of a prescription and lasting for 1 year. Simvastatin and aspirin use were included in the ad- justed models as they have been linked to breastcancer prognosis, and adherence to one medication may correl- ate with adherence to another prescription [33, 34]. Due to the low number of events in the incident model, we used a directed acyclic graph (DAG) to identify the relevant confounders for recurrence (please see Additional file 3). The final DAG adjusted model in- cluded age at diagnosis, UICC stage, chemotherapy, type of primary surgery, and ER/ET status.
Greater cytotoxic potential exhibited in CE contain- ing a higher concentration of phytoalexin compound suggests that purification may improve its anti-cancer properties. Lower IC50 value resulted from higher caf- feine content instead of catechin indicates the purifica- tion method should consider preserving methylxan- thine as a polar constituent, rather than semi-polar flavonoid. Even though IC50 of CE is much lower than doxorubicin and other plant extract, CE might be uti- lized as an anti-cancer agent by using it as a preventive or co-treatment agent. To validate anticancer property of CE, an investigation of immunomodulatory proper- ties, cell sensitization and co-administration with dox- orubicin are required.
Abstract: Statins, or 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors, are medica- tions that have been used for decades to lower cholesterol and to prevent or treat cardiovascular diseases. Since their approval by the US Food and Drug Administration in the 1980s, other potential uses for statins have been speculated on and explored. Basic science and clinical research suggest that statins are also effective in the management of breastcancer. Specifically, in various breastcancer cell lines, statins increase apoptosis and radiosensitivity, inhibit proliferation and invasion, and decrease the metastatic dissemination of tumors. Clinical trials in breastcancer patients support these laboratory findings by demonstrating improved local control and a mor- tality benefit for statin users. A role for statins in the management of aggressive breast cancers with poor outcomes – namely, inflammatory breastcancer and triple-negative breastcancer – is particularly implicated. However, data exist showing that statins may actually promote invasive breast disease after long-term use and thus should be prescribed cautiously. Furthermore, a general consensus on the type of statin that should be administered, for how long, and when in relation to time of diagnosis is lacking. Given their low toxicity profile, affordability, and ease of use, consideration of statins as a therapy for breastcancer patients is imminent. In this review, we summarize current evidence regarding statins and clinical breastcancer outcomes, as well as discuss potential future studies that could shed light on this increasingly relevant topic. Keywords: statins, HMG-CoA reductase inhibitors, breastcancer, inflammatory breastcancer, triple-negative breastcancer, locoregional recurrence
When the data for one disease are not in accordance with each other, they are internally inconsistent. Inconsisten- cies may be caused by differences in the completeness of the data. For example, when more incident cases are missed than deaths, incidence and mortality are inconsist- ent. Also, inconsistencies may arise when the data were derived from different contexts (e.g. a different region) or measured differently (e.g. varying case-definitions). Ap- plying inconsistent incidence and mortality to an IPM model will result in under- or overestimating prevalence, and thus in discrepancies between model estimations and empirical prevalence data. Time trends, on the other hand, may cause the data to appear inconsistent in a steady state model, while in fact they are not. Because prevalence is the resultant of incident cases from the past, it cannot react instantaneously to changes in incidence and case-fatality, but only with a certain delay. It is possi- ble to account for the effects of time trends in a dynamic model, but this requires additional input data on the na- ture and size of the trends, which are not available for most diseases. Often, we do not even know whether a trend is present or not, and the researcher faces a dilemma what to do with the discrepancies. Adjusting observed data for apparent inconsistencies that are in fact the con- sequence of past trends would rather defeat the purpose of IPM models.
Multivariate modelling of the excess mortality rate ratio to take into account selected case-mix factors showed that, as for the unadjusted case, the impact of EP was most marked in the first month after the diagnosis (Table 3). We saw a range in adjusted excess mortality rate ratios between 4.0 (lung) and 20.8 (prostate cancer). The impact of EP fell with time, although EPs still carried a higher risk of mortality at later periods, even when other factors were accounted for. In contrast, the impact of stage on excess mortality either stayed broadly the same within the different time intervals (cervical cancer) or increased with the time since diagnosis (breast, colorectal, lung, and prostate cancer). This difference in the dependence of excess mortality rate ratios on time implies that the causes of mortality following EP are more complex than a simple dependence on tumour stage.
Fewer studies have investigated the influence of statins on cancer recurrence. While a consistent decrement in recur- rence occurs in liver cancer , the findings for most other cancers are equivocal. In breastcancer, however, the majority of clinical evidence supports a protective effect of statins on reducing recurrence . The benefits of statins on reducing breastcancer recurrence appears to be stron- gest in younger patients, suggesting a longitudinal influence of statin therapy . Manthravadi and colleagues demon- strated a 36% reduction in the risk of breastcancer recur- rence in patients taking lipophilic statins . The most convincing evidence in the literature was a population study of all stage I–III breastcancer patients in Denmark conducted by Ahern and colleagues . They found a 10% reduction in breastcancer recurrence among women who were prescribed a lipophilic statin (most commonly simvastatin) but a risk identical to those not on statins among women who were prescribed a hydrophilic statin . These data in aggregate suggest lipophilic statins, and not hydrophilic statins, reduce the risk of breastcancer re- currence, which may indicate a role for statins as agents to impede this mortal stage of tumor progression and second- arily implicate a non-cholesterol effect such as direct tumor cell reduction of prenylation or an indirect effect via reduced inflammatory cytokine release.
In the derivation set, a mixed linear regression model was used to assess the associations between the methyla- tion levels of the selected 3811 CpG sites and 8-isoprostane levels. A natural logarithm transformation of 8-isoprostane levels was employed to ensure normal distribution. The model was adjusted for age (continu- ously), sex (male/female), leukocyte composition using Houseman’s algorithm  (6 continuous variables), al- cohol consumption (continuously), body mass index (BMI, continuously), physical activity (inactive, low, medium, or high), fruit consumption (</≥ once/day), vegetables consumption (</≥ once/day), meat consump- tion (</≥ once/day), smoking status (with seven categor- ies, as shown in Table 1), history of cancer (yes/no), cardiovascular diseases (yes/no), diabetes (yes/no), and asthma (yes/no). Batch-specific variations of the DNA methylation assay were modeled as random effects.