The Role of Patient Factors, Cancer Characteristics, and Treatment Patterns in the Cost of Care for Medicare Beneficiaries with Breast Cancer
Xiao XuJeph HerrinPamela R. SoulosAvantika A. SarafKenneth B. RobertsBrigid K. KilleleaShi‐Yi WangJessica B. LongRong WangXiaomei MaCary P. Gross
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Objective To characterize Medicare expenditures on initial breast cancer care and examine variation in expenditures across hospital referral regions ( HRR s). Data Source We identified 29,110 women with localized breast cancer diagnosed in 2005–2008 and matched controls from the Surveillance, Epidemiology, and End Results‐Medicare linked database. Study Design Using hierarchical generalized linear models, we estimated per patient Medicare expenditure on initial breast cancer care across HRR s and assessed the contribution of patient, cancer, and treatment factors to regional variation via incremental models. Principal Findings Mean Medicare expenditure for initial breast cancer care was $19,255 per patient. The average expenditures varied from $15,053 in the lowest‐spending HRR quintile to $23,480 in the highest‐spending HRR quintile. Patient sociodemographic, comorbidity, and tumor characteristics explained only 1.8 percent of the difference in expenditures between the lowest‐ and highest‐spending quintiles, while use of specific treatment modalities explained 14.5 percent of the difference. Medicare spending on radiation therapy differed the most across the quintiles, with the use of intensity modulated radiation therapy increasing from 1.7 percent in the lowest‐spending quintile to 11.6 percent in the highest‐spending quintile. Conclusions Medicare expenditures on initial breast cancer care vary substantially across regions. Treatment factors are major contributors to the variation.Cite
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Sir,
Oral cancer is a serious and growing problem and it is the sixth most common cancer in the world. In high-risk countries such as Srilanka, India, Pakistan, and Bangladesh, oral cancer is the most common cancer in men and may contribute up to 25% of all new cases.[1] The higher incidence of oral cancer and pre-cancers has been linked with the habit of betel quid and tobacco chewing in India and it is estimated that among the 400 million individuals aged 15 years and above, 47% use tobacco in one form or the other in our country.[2] Patient delay has been cited as the main reason for late attendance and it seems probable that in both the high risk and general population, neither the symptoms of oral cancer, nor the main risk factors are well-understood.[3] Public awareness about the risk factors and methods of early detection of oral cancer is quite low.[3] It has also been observed that chronic tobacco chewers and smokers, who are at a higher risk, do not take advantage of community oral cancer screening programs, if offered. Even if, they come for screening they avoid undergoing for further diagnosis and management. The purpose of this study was to determine the reasons behind the non-attendance and non-compliance of patients with oral pre-cancer and cancer lesions detected in camp screening program for further diagnosis and management at the hospital. This study was approved by an ethical committee of the institute.
We organized oral cancer screening camps at UP State Government Transport Depot, Noida, Ghaziabad and nearby villages. High risk population comprising of drivers, conductors, farmers, and village population using the tobacco in any form were screened for oral pre-cancer and cancer lesions with Magnivisualizer® (magnifying device with white light illumination). Patients with positive lesions were referred to Guru Teg Bahadur (GTB) Hospital (20-40 km away from screening camp sites) for further management where facilities for biopsy and treatment were arranged free of cost. This hospital is a territory hospital having facilities for biopsy, surgery, and radiotherapy. Out of 150 patients diagnosed (with different positive for oral lesions, only 33 (22%) reached at GTB referral Hospital for further management. Remaining 117 (78%) patients refused to go for any management. Owing to social taboos only 3 females came forward for oral cavity examination and one reported to tertiary hospital. This is due to some social restrictions and for females health is not the first priority.
Out of 150 patients, 34 homogenous leukoplakias, 13 non-homogenous leukoplakia, 3 nodular leukoplakia, 2 leukoplakia, 4 oral lichen planus, 88 oral submucus fibrosis 5 other lesions (Candida), and one suspicious for cancer were diagnosed in camp. Each patient has been told about better management facilities of a tertiary hospital, which is attached to a Medical College.
A follow-up survey was conducted to determine the reasons behind the non-compliance of these 117 patients. Telephone numbers, mobile numbers and their contact numbers were already collected during the examination of patients. Patients have been told again and again about the free of cost facilities available in the hospital. These patients were contacted through telephone three to 4 times and were asked for reasons for their non-compliance.
Table 1 shows the reasons behind the non-compliance observed in these patients after the first screening. Shortage of time was the main reason for non-compliance in 27% of patients. Further analysis showed that the long distance of referral hospital from their residence was found to be the main complaint in 20 (17.1%) followed by odd hour duties in 7 (5.9%), and long duty hours in 6 (5.1%) of cases. The next significant reason was denial of any treatment in 18 (15.4%), dependence upon their destiny or fate in 13 (11.1%), addiction for tobacco consumption and non-willingness to leave this habit in 8 (6.8%), fear of time consumption in crowded government hospital or rush in getting medical treatment in 8 (6.8%), fear of diagnosis in 8 (6.8%) of the cases, no support from family and friends in 4 (3.4%), fear of teasing from friends and society in 8 (6.8%) and hesitation to accept treatment in 9 (7.8%) cases were some of the reasons explained by the patients behind the non-compliance and acceptance of treatment. Even 12 (10.3%) of them gave their wrong contact numbers or the contact numbers of their friends during the first screening.
Table 1
Reasons for non-compliance of patients to attend referral hospital after screening for oral cavity
Screenings are organized for 3-5 days, which is too short to build the confidence among patients. Local influential people/village administrative bodies should be included in motivation drive and should be convinced to volunteer themselves to provide means/and facilitate for treatment of patients, who are a farmer and labor. Senior bosses should be also approached to act as a figure head providing leave medical aid for those patients, who are in the job. For distant areas, a mobile van having the facilities for taking a biopsy on the site may be a good option for improving the compliance among patients.
Thus, cancer screening camps alone are not the solutions for any screening programs. A good awareness, involvement of local administrative bodies for follow-up and motivation program should be started before initiating any such program. The reasons behind non-compliance should be looked carefully and the problems should be worked out as far as possible for any successful screening program.
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While comorbidity indices are useful for describing trends in survival, information on specific comorbidities is needed for the clinician advising the individual breast cancer patient on her treatment. Here we present an analysis of overall survival, breast cancer-specific mortality, and effect of medical adjuvant treatment among breast cancer patients suffering from 12 major comorbidities compared with breast cancer patients without comorbidities.The study population was identified from the Danish Breast Cancer Cooperative Group and included 59,673 women without prior cancer diagnosed with early-stage breast cancer in Denmark from 1990 to 2008 with an estimated median potential follow-up of 14 years and 10 months. Information on comorbidity and causes of death was derived from population-based registries. Multivariable proportional hazards regression models were used to assess the effect of comorbidities on mortality, all-cause and breast cancer specific, using patients without comorbidity as reference.At breast cancer diagnosis, 16% of patients had comorbidities and 84% did not. Compared with the latter, the risk of dying from all causes was significantly increased for all types of comorbidity, but the risk of dying from breast cancer was significantly increased only for peripheral vascular disease, dementia, chronic pulmonary disease, liver, and renal diseases. Comorbidities diagnosed within 5 years of breast cancer diagnosis correlated with a greater risk of dying than comorbidities diagnosed more than 5 years before breast cancer diagnosis. With a few exceptions, the effect of adjuvant treatment on breast cancer mortality was similar among patients with and without comorbidity.Breast cancer mortality was not significantly elevated for patients with prior myocardial infarction, congestive heart failure, cerebrovascular disease, connective tissue disease, ulcer disease, and diabetes. The similar effect of adjuvant treatment in patients with and without comorbidity underlines the importance of adhering to guideline therapy.
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BackgroundSurvival of breast cancer patients with comorbidity, compared to those without comorbidity, has been well characterized. The interaction between comorbid diseases and breast cancer, however, has not been well-studied. MethodsFrom Danish nationwide medical registries, we identified all breast cancer patients between 45 and 85 years of age diagnosed from 1994 to 2008. Women without breast cancer were matched to the breast cancer patients on specific comorbid diseases included in the Charlson comorbidity Index (CCI). Interaction contrasts were calculated as a measure of synergistic effect on mortality between comorbidity and breast cancer. ResultsThe study included 47,904 breast cancer patients and 237,938 matched comparison women. In the first year, the strongest interaction between comorbidity and breast cancer was observed in breast cancer patients with a CCI score of ≥4, which accounted for 29 deaths per 1000 person-years. Among individual comorbidities, dementia interacted strongly with breast cancer and accounted for 148 deaths per 1000 person-years within one year of follow-up. There was little interaction between comorbidity and breast cancer during one to five years of follow-up. ConclusionsThere was substantial interaction between comorbid diseases and breast cancer, affecting mortality. Successful treatment of the comorbid diseases or the breast cancer can delay mortality caused by this interaction in breast cancer patients.
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Prevalence of comorbidity at breast cancer diagnosis increases with age and is likely to influence the likelihood of receiving treatment according to guidelines. The aim of this study was to examine the effect of breast cancer treatment on mortality, taking age at diagnosis and comorbidity into account. Four nationwide population registries in Denmark: the Danish Civil Registration System, the Danish Breast Cancer Cooperative Group, the Danish National Patient Register, and the Danish Register of Causes of Death provided information on 62 591 women diagnosed with early-stage breast cancer, 1990–2008, of whom data on treatment were available for 39 943. Comorbidity was measured using the Charlson Comorbidity Index. Adjuvant treatment were categorised as none, chemotherapy, endocrine therapy, and unknown. Multivariable Cox modelling assessed the effect of comorbidity on breast cancer-specific mortality and other cause mortality according to treatment, adjusting for age at diagnosis and other clinical prognostic factors. The impact of comorbidity on mortality was most pronounced in patients aged 50–79 years. Patients receiving chemotherapy with mild to moderate comorbidity had HR 0.99 (95% confidence interval (CI); 0.82–1.19) and 1.06 (95% CI; 0.77–1.46) for breast cancer-specific mortality, respectively, compared with patients without comorbidity. Comorbidity at breast cancer diagnosis is an independent adverse prognostic factor for death after breast cancer. We identified a subgroup of patients with mild to moderate comorbidity receiving chemotherapy who had similar breast cancer mortality as patients with no comorbidity.
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Objective: To determine the effect of comorbidity and stage of disease on 3-year survival in women with primary breast cancer. Design: Longitudinal, observational study. Setting: Metropolitan Detroit. Patients: 936 women ages 40 to 84 years. Measurements: Data on stage of breast cancer, treatment type, and comorbidity were obtained from Metropolitan Detroit Cancer Surveillance System (MDCSS) files and medical records. Personal interviews were the source of information on social and behavioral factors. Vital status and cause of death were obtained from MDCSS files. Results: Patients who had 3 or more of 7 selected comorbid conditions had a 20-fold higher rate of mortality from causes other than breast cancer and a 4-fold higher rate of all-cause mortality when compared with patients who had no comorbid conditions. The effects of comorbidity were independent of age, disease stage, tumor size, histologic type, type of treatment, race, and social and behavioral factors. Moreover, women with severe comorbid conditions had uniformly higher mortality rates, and early diagnosis in these women conferred no survival advantage. Conclusion: Comorbidity in patients with breast cancer appears to be a strong predictor of 3-year survival, independent of the effects of breast cancer stage. This finding suggests that trials assessing the efficacy of screening should routinely include measures of comorbidity.
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