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DIAGNOSIS TO SURGICAL TREATMENT WAITING TIMES FOR NEWLY BREAST CANCER PATIENTS IN LITHUANIA

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Lithuanian University of Health Sciences, Medical Academy

Faculty of Public Health

Department of Preventive Medicine

Teófilo Gutiérrez Higueras

DIAGNOSIS TO SURGICAL TREATMENT WAITING TIMES FOR

NEWLY BREAST CANCER PATIENTS IN LITHUANIA

Master thesis

Scientific supervisor: Prof. Dr. Linas Šumskas

Scientific consultant: Assoc. Prof. Dr. Rugilė Ivanauskienė

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TABLE OF CONTENTS

SUMMARY ... 2 SANTRAUKA ... 3 ACKNOWLEDGMENTS ... 4 CONFLICT OF INTEREST ... 4 ABBREVIATIONS ... 5 1. INTRODUCTION ... 6

2. AIM AND OBJECTIVES ... 7

3. LITERATURE REVIEW ... 7

3.1 General review and timeliness target times ... 7

3.2 Disease progression and survival ... 10

3.3 Importance of time delay ... 11

3.4 Factors, associated with waiting times for breast cancer treatment ... 12

4. MATERIAL AND METHODS ... 14

5. RESULTS AND DISCUSSION ... 15

5.1 Waiting times between histological diagnosis and surgical treatment ... 16

5.2 Demographic and socioeconomic characteristics of the study population and its correlation with the diagnosis to treatment waiting times ... 19

5.3 Clinical characteristics of the study population and its correlation with the diagnosis to treatment waiting times .. 23

6. CONCLUSIONS ... 26

7. PRACTICAL RECOMMENDATIONS ... 27

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SUMMARY

Title: Diagnosis to surgical treatment waiting times for newly breast cancer patients in Lithuania Author: Teófilo Gutiérrez Higueras

Scientific supervisor: Prof. Dr. Linas Šumskas

Aim of the study was: To assess the main demographic, socioeconomic and clinical factors, which could be related with diagnosis-to-treatment waiting times for newly breast cancer patients in Lithuania and to analyze the waiting times as an indicator of accessibility to health care. The objectives of the study were as following: to describe the average waiting time (in days) from diagnosis until surgical treatment in the newly breast cancer patients in Lithuania; to analyze demographic characteristics of patients which could be related with diagnosis to treatment waiting times; to analyze socioeconomic factors of patients which could be related with diagnosis to treatment waiting times.

Material and methods: This was a descriptive analytical cross sectional study. The data was gathered from the Lithuanian National health insurance fund about newly diagnosed breast cancer patients in Lithuania during 2011. The study population was identified from the national database. Women with a primary breast cancer diagnosis registered between January 1, 2011 and December 31, 2011 were eligible for the study sample. The representative sample for this population was based on a finite population size (n=1,560). We have carried out analysis on the sample of 338 patients who answered a survey. The data analyzed included information about the following data: demographic, socioeconomic and clinical variables as well as treatments given to the patients. For our study 11 variables were taken: Date of histological diagnosis, date of surgical treatment, age, place of living, marital status, financial situation, education level, employment status, stage of disease, type of surgery, presence of metastasis.

Results: The average waiting time from histological diagnosis until surgical treatment in Lithuania during 2011 for the newly diagnosed breast cancer women was 46.6 days. Waiting time (in days) in the compared demographical and socioeconomical groups was as following: urban/rural residence – 43.3 vs. 54.5 (p=0.130); married/single – 46.5 vs. 46.8 (p=0.96); employed/retired – 35.7 vs.43.5 (p=0.06); financial situation poor/ very good – 47.8 vs. 53.39 (p=0.92). Waiting time in different clinical groups was: mastectomy/conservative surgery – 64.5 vs. 35.8 (p<0.001); 0-1-2 stage of disease/ 3-4 stage of disease – 3-43,0 vs. 62.5 (p=0.02); no metastasis/yes metastasis – 3-45.3 vs.82.3 (p=0.03-4).

Conclusions: Majority of patients (71.4%) were exposed for longer than the recommended waiting time by the EUSOMA. Longer waiting time was not associated with demographic and socioeconomic characteristics (younger age group less than 40 years, rural place of residence, lower level of education, lower level of income, not regular employment status) in our study. Longer waiting time for surgical treatment was significantly associated with later stage of disease, with presence of metastasis and selection of mastectomy as more radical surgical treatment. Diagnosis to surgical treatment waiting times could be used as indicator for evaluating of quality of health care services.

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SANTRAUKA

Pavadinimas: Susirgusių krūties vėžiu pacienčių laukimo trukmė Lietuvoje nuo ligos diagnozės iki chirurginio gydymo Autorius: Teofilo Gutierrez Higueras

Mokslinis darbo vadovas: Prof. Dr. Linas Šumskas

Tyrimo tikslas ir uždaviniai. Tyrimo tikslas - įvertinti naujų moterų krūties vėžio atvejų pagrindinius socialinius, ekonominius, demografinius ir klinikinius veiksnius, įtakojančius laukimo laiką nuo diagnozavimo iki chirurginės intervencijos Lietuvoje bei aprašyti laukimo laiko reikšmę išgyvenamumui ir sveikatos priežiūros prieinamumui. Tyrimo tikslai tokie: įvertinti laukimo laiką nuo krūties vėžio diagnozės iki chirurginio gydymo; išanalizuoti laukimo laiko sąsajas su demografiniais, socialiniais veiksniais; išanalizuoti sąsajas su klinikiniais veiksniais.

Tyrimo metodika. Buvo atliktas atrinktos pacienčių grupės duomenų analitinis tyrimas. 2011 metų duomenys apie naujas krūties vėžiu sergančias pacientes buvo paimti iš Lietuvos valstybinė ligonių kasos. Šiame darbe tirtos Valstybinės ligonių kasos duomenų bazėje užregistruotos ligonės. Tyrimo imtis – moterys (užregistruotos nuo 2011 m. gruodžio 31 d. – sausio 1 d.), kurioms diagnozuotas krūties vėžys. Respondentų imtis šiame darbe susieta su baigtiniu šalies populiacijos dydžiu. Buvo ištirti 338 atvejai.

Iš duomenų bazės buvo paimti šių ligonių socialiniai, demografiniai duomenys, klinikinė informacija apie pacienčių gydymą. Surinkti duomenys apėmė 11 kintamųjų: histologinį tyrimą, chirurginio gydymo būdą, amžių, gyvenamąją vietą, šeimyninę padėtį, finansinę padėtį, išsilavinimą, užimtumas, ligos stadiją, metastazių pasireiškimą.

Rezultatai. Naujoms pacientėms, kurioms 2011 m. buvo diagnozuotas krūties vėžys, nuo ligos nustatymo pradžios iki chirurginio gydymo pradžios vidutiniškai reikėjo laukti 46,6 dienas. Laukimo laikas dienomis atitinkamose demografinėse ir socialinėse-ekonominėse grupėse pasiskirstė taip: miestas / kaimo vietovė - 43,3 ir 54,5 (p = 0,130); ištekėjusios / vienišos - 46,5 ir 46,8 (p = 0.96); dirbančios / nedirbančios - 35,7 ir 43.5 (p = 0,06); finansinė padėtis prasta / labai gera - 47,8 ir 53.39 (p = 0.92). Operacijos laukimo laikas dienomis skirtingose klinikinėse grupėse buvo toks: taikyta mastektomija / konservatyvi chirurgija - 64,5 ir 35,8 (p <0,001); 0-1-2 ligos stadija / 3-4 ligos stadija - 43,0 ir 62,5 (p = 0,02); nėra metastazių / yra metastazės - 45,3 ir 82.3 (p = 0,04).

Išvados. Didžioji dalis pacienčių (71.4%), kurioms diagnozuotas krūties vėžys, radikalios chirurginės intervencijos laukė ilgiau negu numatyta tarptautinėse EUSOMA rekomendacijose. Mūsų tyrime ilgesnis laukimo laikas nebuvo susijęs su

demografiniais ir socialiniais-ekonominiais veiksniais (su jaunesniu amžiumi - iki 40 metų, gyvenamąja vieta kaimo vietovėje, su žemesniu išsilavinimu, mažesnėmis pajamomis bei su nedalyvavimu darbo rinkoje). Ilgesnis chirurginės intervencijos laukimo laikas buvo statistiškai patikimai susijęs su vėlesne ligos stadija, su metastazių buvimu. Taip pat ilgesnį laukimo laiką apsprendė pasirinkta radikalesnė gydymo strategija (mastektomija) lyginant su labiau tausojančiu chirurginio gydymu. Atlikta analizė leidžia daryti išvadą, kad laukimo laikas nuo histologinės diagnozės iki chirurginio gydymo gali būti naudojamas kaip svarbus sveikatos priežiūros

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ETHICS COMMITTEE APPROVAL

Biomedical Research Ethics Committee permission no. BEC-MF-319 was received with issue date February 28, 2017. State Data of patient’s case histories permission from the service of medical statistics no. TP-1987 was received with issue date June 9, 2016.

ACKNOWLEDGMENTS

The author is grateful to the Lithuanian Cancer Registry, National Health Insurance Fund, and the Hospital of Lithuanian University of Health Sciences (LSMU), Kauno klinikos for providing the data.

CONFLICT OF INTEREST

The author reports no conflicts of interest.

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ABBREVIATIONS

NHS National Health Service of United Kingdom, EUSOMA European Society of Breast Cancer Specialists NICCQ National Initiative on Cancer Care Quality

INCA Instituto Nacional de Câncer José Alencar Gomes da Silva CIHI Canadian Institute for Health Information.

OS Overall survival

PFS Progression-free survival GHC Old Ghanaian Cedi PTD Patient delay time BSE Breast self-examination WT Waiting time

BCS Breast conservative surgery MRI Magnetic resonance imaging PET Positron emission tomography

SEER The Surveillance, Epidemiology, and End Results NCBC National Consortium of Breast Centers

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1. INTRODUCTION

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females worldwide, with an estimated 1.7 million cases and 521,900 deaths in 2012. Breast cancer alone accounts for 25% of all cancer cases and 15% of all cancer deaths among females. [1]

More developed countries account for about one-half of all breast cancer cases and 38% of deaths. Rates are generally high in Northern America, Australia/New Zealand, and Northern and Western Europe; intermediate in Central and Eastern Europe, Latin America, and the Caribbean; and low in most of Africa and Asia.

Approximately near 500 000 new cases of breast cancer are registered in Europe annually. In Lithuania incidence, according last data of 2012 is nearly 1550 cases per year. [2]

The diagnosis of breast cancer is based on the results of clinical, radiological, and patho-morphological examinations. Breast self-examination is considered an “optional” screening tool done by the patient after menstruation, while the mammography is considered to be the standard main screening method in case of found lumps, or in different screening programs in women aged 50-69 years old.

Delayed treatment, is considered an independent negative prognostic factor because it results in shorter survival [3]. This is why the European Society of Breast Cancer (EUSOMA) has recommended that no more than 15 days should be a waiting time period between diagnosis and treatment, being the desirable time less than 10 days [4].

Increased waiting times between diagnosis and treatment are related with multiple socioeconomic, demographic and clinical factors that could contribute to a survival decrease in newly diagnosed breast cancer patients.

However, incidence and mortality rates are decreasing in developed countries because of early detection and improved treatment [5, 6]. In contrast, in the developing world, lack of public awareness, absence of organized screening programs and lack of accessible and effective treatment for BC are cited as reasons for delays in treatment and higher mortality rates [7].

For the evaluation of these factors, we have performed a descriptive observational cross sectional study about newly diagnosed breast cancer patients in Lithuania during 2011. We were aiming to get better insight into diagnosis-to-treatment waiting times for newly breast cancer patients in Lithuania. We made hypothesis that waiting times are related with different demographic, social, economic and clinical characteristics. These possible determinants are important to know for field practices in health care.

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2. AIM AND OBJECTIVES

The aim of the study was:

To assess the main demographic, socioeconomic and clinical factors, which could be related with diagnosis-to-treatment waiting times for newly breast cancer patients in Lithuania and to analyze the waiting times as an indicator of accessibility to health care.

The objectives of the study:

1. To describe the average waiting time (in days) from diagnosis until surgical treatment in the newly breast cancer patients in Lithuania.

2. To analyze demographic factors, which could be related with diagnosis-to-treatment waiting times.

3. To analyze socioeconomic factors, which could be related and clinical factors, which could be related with diagnosis-to-treatment waiting times

3. LITERATURE REVIEW

3.1 General review and timeliness target times

Most guidelines recommend starting treatment as soon as possible after breast cancer is diagnosed. Timely treatment reduces the risk that the cancer will spread and increases the chances for survival.

In an American study, waiting 60 days or more to start treatment after diagnosis was associated with a significant 66 and 85% increased risk of overall and BC-related death, respectively, in low-income late-stage patients. [3].

In another American study [8] looking at when women had surgery, the researchers looked at medical records in two databases:

1. The Surveillance, Epidemiology, and End Results (SEER) database, which is a large registry of cancer cases from sources throughout the United States maintained by the National Institutes of Health; this database also is linked to Medicare information.

2. The National Cancer Data Base, which contains information from more than 1,500 cancer facilities and is sponsored by the American College of Physicians and the American Cancer Society.

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8 From the SEER database, the researchers looked at the records of 94,544 people age 66 or older who were diagnosed with primary stage I to stage III breast cancer from 1992 to 2009:

- 77.7% had surgery 30 or fewer days after diagnosis - 18.3% had surgery 31 to 60 days after diagnosis - 2.7% had surgery 61 to 90 days after diagnosis - 0.7% had surgery 91 to 120 days after diagnosis - 0.5% had surgery 121 to 180 days after diagnosis

Overall, after the first 30 days after diagnosis, each 30-day delay in surgery was associated with a 9% decrease in survival. So the longer women delayed surgery, the worse survival they had. This worse survival was statistically significant for women diagnosed with stage I and stage II disease. This means that the difference in survival was likely due to the delay in surgery and not just due to chance.

From the National Cancer Data Base, the researchers looked at the records of 115,790 people age 18 or older who were diagnosed with no metastatic, no inflammatory breast cancer between 2003 and 2005:

- 69.5% had surgery 30 or fewer days after diagnosis - 24.9% had surgery 31 to 60 days after diagnosis - 4.1% had surgery 61 to 90 days after diagnosis - 1% had surgery 91 to 120 days after diagnosis - 0.5% had surgery 121 to 180 days after diagnosis

Overall, after the first 30 days after diagnosis, each 30-day delay in surgery was associated with a 10% decrease in survival. This difference in survival also was statistically significant. The difference in survival was highest in women diagnosed with stage I and stage II disease.

Practice guidelines for breast cancer emphasize that the work-up of a lump in the breast should be completed as soon as possible after detection. [9]

Currently there is no agreement on what the optimal time to treatment should be, and decisions of both patients and health care providers influence the time from detection to treatment. Delays can arise if a woman is reluctant to seek medical follow-up for a suspicious breast lesion or if health care providers are unable to evaluate and treat the lesion as quickly as they might wish. Evidence is lacking on the minimum delay that would have a negative impact on survival.

Sainsbury and associates, [10] in a retrospective analysis of data for 36 222 patients in Great Britain, found no evidence that delays of more than 90 days from family physician referral to treatment adversely affected survival. Indeed, they found that shorter delays were associated with poorer survival, likely reflecting more rapid treatment for women presenting with advanced disease. Nevertheless, Great Britain has recommended that all patients presenting with suspected breast cancer must be seen within 14 days

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9 after referral. Australian authorities [11] argue instead that arriving at an appropriate treatment decision is a more important influence than speed on the outcome of breast cancer.

A meta-analysis [12] of data from 87 nonexperimental studies involving over 100 000 patients showed that women who delayed seeking medical attention for 3 months or more had a 12% lower 5-year survival rate than those who presented sooner (odds ratio 1.47; 95% confidence interval [CI] 1.42 to 1.53). The poorer survival was likely mediated through a mechanism that the authors referred to as “stage-drift,” whereby women presenting later have more advanced disease, which makes stage an intermediate variable between delay and outcome. Although only patient delay was examined, the authors’ overall conclusion was that efforts should be made to keep delays by patients and health care providers to a minimum.

Many organizations have emphasized the value of timeliness. [13-20]. The Agency for Healthcare Research and Quality defines timeliness as “the health care system's capacity to provide care quickly after a need is recognized.” The American Medical Association and the National Consortium of Breast Centers (NCBC) have included “timely care” in their definitions of quality care. The NCBC has described multiple time intervals that occur during the diagnostic evaluation and treatment of patients with breast cancer. Measurement of 7 of these time intervals has been included, along with 24 other quality indicators, to create the NCBC's National Quality Measures for Breast Centers program (NQMBC). The investigation of timeliness of care provided to breast cancer patients is important because, as others have reported, patients and referring care providers expect rapid access to care for breast problems. In addition, disturbing disparities in access and wait times for diagnosis and treatment have been documented. The emphasis for prompt diagnosis and treatment has been highlighted in recent updates of care guidelines published by oncology organizations. The recommendations of these organizations are not uniform, and they are based largely on professional opinion because the literature describing the relationship between patient satisfaction and timeliness is scant. The recommended timeliness targets published by professional organizations are provided in Table 1.

Table 1: Timeliness targets for breast cancer diagnosis to surgical treatment waiting times in different countries

Country (Source) Time interval Timeliness target (Days)

England (NHS) [16] Diagnosis to treatment ≤31 days

European Union (EUSOMA) [4] Decision to operate and date offered surgery

Acceptable, <15 days, desirable, <10 days

United States (NICCQ)[18] Decision made for surgery to surgery date ≤21 days in 90% of patients

Brazil (INCA)[19] Diagnosis to treatment ≤60 days

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10 NHS, National Health Service of United Kingdom; EUSOMA, European Society of Breast Cancer Specialists; NICCQ, National Initiative on Cancer Care Quality; INCA, Instituto Nacional de Câncer José Alencar Gomes da Silva; CIHI, Canadian Institute for Health Information.

3.2 Disease progression and survival

Chances for survival vary by stage of breast cancer. Non-invasive (stage 0) and early stage invasive breast cancers (stages I and II) have a better prognosis than later stage cancers (stages III and IV). In addition, cancer that has not spread beyond the breast has a better prognosis than cancer that has spread to the lymph nodes.

The poorest prognosis is for metastatic breast cancer (stage IV), where the cancer has spread beyond the lymph nodes to other parts of the body. According National Cancer Institute of the United States [21]:

Overall survival (OS) has been historically considered the most important therapeutic objective in advanced breast cancer. However, survival may be influenced by therapies used after patient participation in a given trial, thus making OS a less useful trial end point in an era of effective subsequent-line agents. Indeed, some randomized trials in advanced breast cancer are underpowered to detect plausible OS differences, and OS gain has reportedly been achieved only occasionally in the hundreds of randomized trials conducted to date in advanced breast cancer. In contrast, many recent trials in this disease have used progression-free survival (PFS) or time to tumor progression (TTP) as the primary end points [22]. In a prospective translational study in Slovakia, the presence of circulating tumor cells in patients with metastatic carcinoma was associated with short survival. [23]

A prospective trial at 20 clinical centers in the United States [24] showed that in metastatic breast cancer before any treatment, for all 177 patients, the median progression-free survival was approximately 5.0 months (95 percent confidence interval, 4.0 to 6.4) and the median overall survival was more than 18 months (95 percent confidence interval, 14.6 to >18). Of 177 patients, 87 (49 percent) had ≥5 circulating tumor cells per 7.5 ml of blood at baseline. These 87 patients had a significantly shorter median progression-free survival (approximately 2.7 months; 95 percent confidence interval, 2.1 to 4.4) and median overall survival (approximately 10.1 months; 95 percent confidence interval, 6.3 to 14.6) than did patients with <5 circulating tumor cells per 7.5 ml of blood (median progression-free survival, approximately 7.0 months; 95 percent confidence interval, 5.8 to 8.9; overall survival, >18 months)

After initial treatment of the 163 remaining patients, 49 (30 percent) with ≥5 circulating tumor cells per 7.5 ml of blood at the first follow-up visit had a significantly shorter median progression-free survival (approximately 2.1 months; 95 percent confidence interval, 1.8 to 2.5) and a shorter median overall survival (approximately 8.2 months; 95 percent confidence interval, 5.6 to 11.1) than did the 114 patients (70 percent) with <5 circulating tumor cells per 7.5 ml of blood (progression-free survival, approximately 7.0 months; 95 percent confidence interval, 5.8 to 8.4; overall survival, >18 months)

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11 The outlook for women with breast cancer varies by the stage (extent) of the cancer. In general, the survival rates are higher for women with earlier stage cancers. But remember, the outlook for each woman is specific to her circumstances.

The 5-year relative survival rate for women with stage 0 or stage I breast cancer is close to 100%. For women with stage II breast cancer, the 5-year relative survival rate is about 93%.

The 5-year relative survival rate for stage III breast cancers is about 72%. But often, women with these breast cancers can be successfully treated.

Breast cancers that have spread to other parts of the body are more difficult to treat and tend to have a poorer outlook. Metastatic, or stage IV breast cancers, have a 5-year relative survival rate of about 22%. Still, there are often many treatment options available for women with this stage of breast cancer. [21]

3.3 Importance of time delay

The natural history and clinical relevance of breast cancer vary significantly. In view of tumor progression, in addition to staging or biomarker levels, the natural history of the tumor may have the potential to better define the biological nature of the disease process, regarding risk as well as therapy.

A long duration of symptoms was found to be associated with tumor progression, including tumor size, lymph node metastasis and disease recurrence, in patients with breast cancer. These results suggest that the progression of breast cancer is dependent on time. Thus, a long duration of symptoms may be considered as an indicator of tumor progression and may be a significant prognostic factor in breast cancer. These findings are consistent with the consensus reached by previous studies, namely that longer delays in treatment are associated with larger tumor size and more advanced stage.

The practical significance of these findings is that reducing the delay in presentation and treatment may lead to improved prognosis of patients who present with symptomatic breast cancer. It has been demonstrated that patients with cancer detected upon screening exhibit an improved overall survival and reduced recurrent disease compared with patients with cancers detected following the onset of symptoms [25]. Effective strategies should be developed for early detection of breast cancer, in order to reduce the duration of symptoms. However, the effect of a symptom duration of <6 months is likely to be limited.

A major concern with studies investigating the effect of delay on survival is that the potential confounding effect of lead time bias is not taken into consideration. For patients who eventually succumb to cancer, the interval between treatment and death is shorter if treatment is initiated later in the course of the disease.

Longer delays between symptom onset and treatment were found to adversely affect survival, which may be attributed to greater tumor progression at treatment initiation.

Breast cancer progression is dependent on time and that symptom duration may be a strong prognostic factor in breast cancer patients. A longer duration of symptoms may be considered an indicator of tumor progression and such patients may require more aggressive adjuvant therapies due to the higher risk of distant recurrence. [26]

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3.4 Factors, associated with waiting times for breast cancer treatment

In a retrospective study in Ghana in 2013 [27] the disease stage and health insurance status were associated with median waiting time from presentation to start of definitive treatment. Specifically, patients with stages III and IV had shorter waiting time than those with stages I and II (4 weeks and 7 weeks, respectively).

Also, the median waiting time for those who had health insurance (6 weeks) was higher than those without health insurance (4 weeks). The median waiting time did not differ by sex, age, marital status, level of education, ethnicity, religion, and income of the patients.

However, those who were married or cohabiting had lower median waiting time compared with those who were single, although this was not statistically significant. Furthermore, the median waiting time reduced with higher level of education such that those with higher education had the lowest median waiting time to start of definitive treatment (also not statistically significant).

Health Care Worker and Health System Factors also could have influence on waiting time. The results show that—the health care worker factors were not significantly associated with median waiting time to treatment. However, two health system factors were associated with median waiting time. Specifically, there was significant difference in the waiting time depending on the sites of treatment.

Patients recruited from the surgery site had higher median waiting time in the start of definitive treatment compared with patients who received care at the oncology site (6 weeks and 4 weeks, respectively. Furthermore, the median time interval between when biopsy was requested and when results were received was 6.0 weeks. There was a significant positive correlation between waiting time for biopsy results and waiting time in the start of definitive treatment.

The magnitude of the association between waiting time for biopsy results and start of treatment was r = .348 (p = .001). The study shows that level of education, age, income, marital status, ethnicity, disease stage, health insurance status, study sites, time interval between when biopsy was requested and when results were received, and receipt of adequate information from health workers were the determinants of waiting time from presentation to start of definitive treatment. However, religion was not significantly related to waiting time to start of definitive treatment.

Specifically, the results show that those with middle/ junior high school, secondary/senior high school and postsecondary education had significantly shorter waiting time than those with no education (44.6%, 39.2%, and 35.4%, respectively).

Also, those who were 50 to 59 years and 60 to 69 years had significantly longer waiting time than those who were aged 40 years and younger. However, there was no significant difference in waiting time between those who were 40 and 49 years and those who were aged 40 years and younger. Furthermore, those with no income and those who earned less than 1,000 GHC (Old Ghanaian Cedi) had significantly longer waiting time than those who earned GHC 2,000 and above. With regard to marital status, those who were single had 21% longer waiting time to start of definitive treatment compared with those who were married.

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13 With respect to the disease stage, those with stage I and II had significantly shorter waiting time (IRR = 0.588, p < .001) than those with stage III and IV. Also, breast cancer patients recruited from the oncology site had significantly longer waiting time than those recruited from the surgery site (IRR = 1.231, p < 0.05).

In addition, a unit increase in the time between when biopsy was requested and when results were received increases the waiting time in the start of definitive treatment by 2.2% (IRR = 1.022, p < 0.001). Also, the waiting time for those who received adequate information from the health workers was 61.1% shorter than that of those without adequate information from the health workers.

In a Canadian study, [28] among the determinants of delay for BC diagnosis, a longer WT was evidenced for women with lower family income, but it was the only significant variable among all the economic factors studied (marital status, socio-sanitary region, education, working status). A significant association between lower socio-economic status and longer surgical WTs was also reported in California [29] and Colombia [30].

Another study in Turkey [31] shows that factors found to influence patient delay time were distrust of the health-care system, disregarding symptoms, lack of breast self-examination (BSE) and a low level of education. [32]

Longer PDTs (Patient delay time) in developed countries were found to be associated with older age (>65 years), lower education (≤5 years), lack of routine breast examinations and health-care providers. [33]

In the study, was found that longer PDT was correlated with disregarding the detected symptoms and belonging to the age group 30–39. Shorter PDT’s were predicted by regular BSE, family and friend’s support and at least secondary education, which was consistent with our previous international survey.

Demographic findings showed that almost half of our patients were premenopausal, and 16% of them were younger than 40 years. These differences may be related to a younger population in Turkey because the percentage of women aged <40 years is 65%, as compared with 45% in the USA

Another Polish study [34] shows that the average waiting time for treatment varied depending on the age group. In the group aged 15-49, it was 38 days, in the group aged 50-69 – 35 days, and in the oldest group– 52 days. The waiting time for first treatment was the longest for the patients with a local stage – approximately 45 days; patients with a regional stage waited for 33 days, while those with a metastatic stage – 11 days. Urban women waited for approximately 40 days for the first treatment, and rural women waited less, for approximately 31 days.

A French study [35] shows that younger patients experienced a shorter WT (Waiting time) than older. Inappropriate reassurance that a palpable mass is benign, difficulties in mammography detection and late biopsy were reported as the main explanations of longer WT in young patients.

In general, the faster the treatment is initiated in a patient with breast cancer the longer survival times were reported. Also sociodemographic and clinical factors like age, place of living, income status, clinical stage…, may play an important role increasing or decreasing WT between diagnosis and initial treatment of breast cancer.

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4.

MATERIAL AND METHODS

This is a descriptive observational cross sectional study, which was based on the existing health care information. The data was collected from the Lithuanian National Health Insurance Fund about newly diagnosed breast cancer patients in Lithuania during 2011.

Study population.

The study population was identified from the national database of the Lithuanian National Health Insurance Fund and a survey collected from 338 newly diagnosed breast cancer patients in Lithuania. Women with a primary breast cancer diagnosis registered between January 1, 2011 and December 31, 2011 were treated as potentially eligible persons for the study sample. The representative sample for this population was based on a finite population size (n =1,560). Cases with incomplete records of the variables related to time were excluded (case records were examined to understand reasons for this non-completeness).

Variables analyzed.

The database included information about these patients' personal data: sociodemographic-socioeconomic and clinical variables as well as treatments given to the patients. 11 variables were taken for our study:

- Age - Place of living - Marital status - Financial situation - Education level - Employment status

- Stage of breast cancer

- Type of surgery applied

- Presence or absence of metastasis

- Date of histological diagnosis

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15 Age was calculated in years and month according the date of birth. We have used two categories to classify women according the place of residence – urban (town, city) or rural (small towns, villages, countryside). We also checked the marital status, which received two categories, Married or lives in partnership and Single, widowed, or divorced. In terms of education level, we differentiate three categories, primary or comprehensive; Secondary or further and not completed higher or higher. We also differentiate employment status in three other categories, actively working; Retirement / pension and sickness / disability. Finally, we check the Financial situation that can be poor, good or very good.

Statistical analysis.

The results were analyzed using univariate statistics (calculations of frequency, mean, median, standard deviation, minimum, maximum and range). For the association between time and the variables of the study, comparison of means were used. Besides, we evaluate fit or no to a normal distribution with the Kolmogorov-Smirnov test. If the fit is no adjustment to the normality, we used non-parametric test Mann-Whitney-Wilcoxon and Kruskal–Wallis H test (when the fit had 3 categories or more). The difference between the studied variables was considered statically significant when p <0.05.

The software used for statistical analysis of the data was the IBM statistical package SPSS Statistics 20.0.

5. RESULTS AND DISCUSSION

A sample of 338 women diagnosed of breast cancer during 2011 in Lithuania was studied. Table 2 presents the social-demographic and socio-economic characteristics of the subjects. The subjects’ mean age was 58.8 (SD, 12.8). According age groups, the interval of women between 50-59 years has the higher frequency (28.4%) of new BC cases.

The majority (238 or 70.4%) of the subjects indicated that they lived in the city. A greater part of the subjects lived in families or with partners (57.7%), and approximately 70% of them had acquired secondary or further education levels. According employment status, only near 30% of women are actively working, the rest are pensioner or disable to work. Near 50% of the women consider that their financial situation is good versus near 40% of the women that consider that their economic situation is poor.

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Table 2: Demographic and socioeconomic characteristics of the study sample (n=338)

5.1 Waiting times between histological diagnosis and surgical treatment

In the Table 2, we performed descriptive statistics with the central tendency measures like mean, median and mode. Later, we analyzed dispersion measures of dispersion like range and standard deviation to be able to evaluate the characteristics that define the sample formed by 308 of breast cancer patients. We had to exclude 30 women from the sample who did not meet the time requirements due to 20 of them were not operated and 10 of them were treated before being diagnosed.

Sociodemographic and socioeconomic variables Distribution of subjects N (%) Mean Standard deviation (SD) Number of responders

Age (in years) 58.8 12.8 338 Age groups: <40 40-49 50-59 60-69 >70 23 (6.8) 57 (16.9) 96 (28.4) 89 (26.3) 73 (21.6) Place of residence 338 Urban Rural 238 (70.4) 100 (29.6) Marital status 338 Married or lives in partnership Single, widowed, or divorced 195 (57.7) 143 (43.3) Education level 336 Primary or comprehensive Secondary or further Not completed higher or higher 102 (30.2) 119 (35.2) 115 (34.0) Employment status Actively working Retirement/pension Sickness/disability 91 (26.9) 139 (41.1) 108 (32.0) 338 Financial situation 338 Poor Good Very good 131 (38.8) 162 (47.9) 45 (13.3)

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17 According time, the arithmetical mean value of this variable shows a waiting time between histological diagnosis and surgical treatment of 46.59 days for the newly breast cancer affected patients in Lithuania during 2011.

This waiting time is much higher than the desirable time of 15 days recommended in the European Union [4] and higher than the median time of 15 days in Germany [36] and 21.5 days in Kenya [37]. However, it is lower than 11.1 weeks reported by Jassem et al. [38] for 12 countries in low- and middle-income countries excluding Africa. In other study in Brazil timeliness target of 12 weeks [19].

Analyzing the mode, we got a value of 0 days that indicates that the major majority of time between the diagnosis and the treatment is 0 days with a value of 9.5% for a minimum value of 0 days and a maximum value of 458 days. This mode value of 0 days is due to many women after biopsy are appointed for the results, and in the case of positive in cancer, the surgery is performed in the same day after receiving the results.

The measure of dispersion standard deviation is perceived as somewhat high although does not become so high as to remove reliability to the observed mean value, a circumstance that allows to conclude that there is a certain heterogeneity between the time of diagnosis and surgical treatment in relation to the newly 308 women diagnosed with breast cancer.

Table 3: Diagnosis to surgical treatment mean waiting times in breast cancer patients

N Range Minimum Maximum Mean Standard deviation

Diagnosis to Surgical treatment

time 308 458 0 458 46.59 58.96

In the Fig.1 our study also showed that close to 55% of the patients were operated by 4 weeks; this is similar than the one observed in Germany in which 59.4% of patients started treatment within 4 weeks [36].

About 15% waited for more than 3 months to start treatment in our study. This is higher than that observed in a German study in which only 11% waited for more than 3 months. These waiting times shown that approximately half of the patients in our study will be associated with decrease in survival according an American study [8] in which after the first 30 days after diagnosis, each 30-day delay in surgery was associated with a 10% in decrease survival.

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Fig.1 Waiting time between diagnosis and surgical treatment: distribution of clinical groups by days on a waiting list

In the Fig.1 the first thing we observe in the histogram is a positive asymmetric distribution to the right, since the tail of the bell curve tends to fall sharply in the zone of the highest values with respect to the number of days, valuating that if we compare it with the characteristics that identify the Gaussian bell curve, the mean with a value of 46.59 days is already far from the value of mode, the highest value of the distribution, and the value of the median, concluding that most of the data in our sample are located in the area of the left, a zone of lower values in relation to the time between the diagnosis and the treatment.

We could say that the observed data of the histogram evaluates an adjustment to a remote distribution of the Gaussian bell curve, in terms of degree of symmetry and pointing of the curve, since the kurtosis is perceived quite platykurtic with values somewhat far from the value of the mean, evaluating a certain dispersion between the subjects in relation to the time of diagnosis and its treatment.

After observing the non-compliance of symmetry and the typical mesokurtic kurtosis or belliform kurtosis of a normal distribution, we could say that the variable time in relation to the 308 women treated for breast cancer, there is heterogeneity in relation to their value observed in the central measurements as the mean, median and mode, data that allows me to conclude that the study sample presents different times between the diagnosis and the treatment, valuing that perhaps there is more concentration of women in a shorter time between the diagnosis and subsequent treatment.

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Fig. 2. Histogram of time between diagnosis and surgical treatment.

5.2 Demographic and socioeconomic characteristics of the study population and its correlation with the diagnosis to treatment waiting times

The analysis of mean scores of the diagnosis-to-treatment waiting times of the socioeconomic and sociodemographic parameters of newly diagnosed breast cancer patients are shown in the Table 4. We had to exclude 30 women from the sample who did not meet the time requirements due to 21 of them were not operated and 9 of them were treated before being diagnosed.

All the variables have a significance level of 0.05, being able to evaluate that there is no adjustment to normality and therefore there is no normality, so we can evaluate non-parametric tests.

Age group. The objective to intending relate the age groups and the WTs was contrast the hypothesis of the existence of

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Table 4: Distribution of the mean waiting time between diagnosis to surgical treatment by demographic and socioeconomic characteristics of patients (n=308)

Demographic and socioeconomic characteristics Mean Distribution of subjects N Distribution of subjects (%) Number of responders p-value Chi-square Age 308 Age group: 0.395 <40 74.00 22 7.1% 40-49 38.20 54 17.5% 464.96 50-59 46.47 86 27.9% 60-69 46.81 83 26.9% >70 44.08 63 20.5% Place of residence 308 Urban 43.32 218 70.8% 0.130 115.09 Rural 54.51 90 29.2% Marital status 308 Married or lives in partnership 46.46 179 58.1% 0.964 120.59 Single, widowed, or divorced 46.77 129 41.9% Education level 306 Primary or comprehensive 50.09 91 29.7% 0.313 Secondary or further 46.50 111 36.3% 2.122 Not completed higher or

higher 41.63 104 34.0% Employment status 308 Actively working 35.71 82 26.6% 0.06 1.797 Retirement/pension 43.48 126 40.9% Sickness/disability 59.42 100 32.5% Financial situation 304 Poor 47.76 120 39.5% 0.917 Good 43.91 146 48.0% 204.61 Very good 52.39 38 12.5%

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21 For it, first we evaluate the fit or not to a normal distribution, is evaluated the data of the Kolmogorov-Smirnov test (KS-test); as the level of significance is less than 0.05, we evaluate that there is no adjustment to the normality, that allow us to evaluate the alternative non-parametric test called Kruskal–Wallis H.

As the level of significance is greater than 0.05 (p=0.395) for a CI (confidence interval) of 95% margin of error, we estimate that there is not too much heterogeneity in the means of the recoded age categories for the variable time in relation to the time between the diagnosis and treatment.

We found that patients in the age group of less than 40 years had an average of 74 days between diagnosis and treatment, which gives us the highest mean. In contrast, the age group of women aged 49-49 years had the lowest mean, with 38.20 days between treatment and diagnosis. The rest of age groups has a similar average that is around 45 days. The standard deviation allows to evaluate if there is a great distance or dispersion of the evaluated groups from the value of the mean, determining that the highest standard deviation is valued with a data of 23.9 in the group of women with less than 40 years old, circumstance that gives less reliability to the value of mean, because when more dispersion, the mean will be more heterogeneous. Despite the observed differences the statistical analysis showed no statistical significance of the observed differences (p=0.395).

Our results are only partially similar with study in Poland [34], showing that the group aged 15-49 had a WT of 38 days, in the group 50-69 years – 35 days, and in the oldest group – 52 days. Therefore, the similar study in Ghana [27] have reported that in women between 50 to 59 years and 60 to 69 years had significantly longer waiting time than those who were aged 40 years and younger. At the same time, we should take into account that access to health care in majority of developing countries is poor and not comparable with the European countries.

We suppose that young people could have longer waiting times in many countries due it’s not so frequent to develop breast cancer in younger patients and due to lack of mammographic screening programs for young women. According to the European Guidelines, tracking by mammography should take place every two years, in the target group of women aged 50 to 69 years old [39]. In contrast, countries with good informative programs about BSE, the delay tended to be slightly less common among women who reported at least monthly breast self-examination [40]. Another consideration is that because of cosmetic considerations, younger women may take longer to decide between a lumpectomy or mastectomy after a cancer diagnosis.

Place of residence. The objective to relate the place of living and the WTs was contrast the hypothesis of the existence of difference of means between people living in urban vs. rural areas and the variable time between diagnosis and treatment. To evaluate the fit or not to a normal distribution, is evaluated the data of the Kolmogorov-Smirnov test (KS-test); as the level of significance is less than 0'05, we evaluate that there is no adjustment to the normality, that allow us to evaluate the alternative non-parametric test called Mann-Whitney-Wilcoxon, in which we observe a significance level more than 0.05 (= 0.130) for a CI of 95% distributed margin of error with a Z value lower than 1.96 (-1.989). All this means that between the urban population and the rural population with BC there are no significant differences in the waiting time between the diagnosis and the surgery.

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22 Even so, the mean of days for the rural population in relation to the number of days between the diagnosis and the surgical treatment has a value of 54.51 days. This means that the people in the countryside wait more days between its diagnosis and its treatment, valuing that the people living in urban areas has mean of has 43.32 days between the diagnosis and the surgical treatment.

Analyzing different related researches, we found that one of reasons for differences in cancer waiting times for people in nonmetropolitan regions is reduced access to cancer treatment. This can be due to poorer geographical access to health care facilities, including inadequate transport links, also it could be the effect of less developed cancer screening and diagnostic services it rural areas. [41]

Marital status. As the level of significance is greater than 0.05 (p = 0.964), indicated that between the married group and

the unmarried group there are no significant differences in the waiting times between the diagnosis and surgery. With a value Z lower than 1.96 (0.104), concluding in the table of ranges that the average range is hardly divergent between being single and married and the variable time between diagnosis and treatment.

For the variable marital status, the mean for singles is a little higher with an average of 46.77 days between diagnosis and treatment, on the other hand for married couples the mean is 46.46. Valuing a standard deviation higher for married couples (61,984) than singles (64.729).

In a similar study in Canada [29], the variable marital status was not related with longer waiting times. In contrast in other study [27] women married or cohabiting had lower median waiting time compared with those who were single, although this was not statistically significant.

Education level. Evaluating the level of significance and the means in time between different educational levels, first of all

we performed a non-parametric test, Kruskal–Wallis H that allow us to assess if there is any difference between women with breast cancer who have primary, secondary or university studies in relation to the waiting time.

The Kruskal–Wallis H distribution test with a significance level of 0.05 (p = 0.313) and a chi-square value 2.122. These statistical values mean that there isn’t a significant difference between the values of waiting time in the different levels of education.

For the variable educational level, the most outstanding mean is in the group of primary level education with an average of 50.09 followed by the secondary category with an average of 46.50 days between the histological diagnosis and surgical treatment. Assuming that the standard deviation is also higher in the women with primary studies (67.885). High educational level present the lowest average in waiting times between diagnosis and treatment with a value of 41.63 days.

Consistent with our results, a low level of education was found to be related to longer WTs in many studies [42-44].

Employment status. The Kruskal–Wallis H distribution test with a significance level of 0.05 with (p= 0.06), a chi square

1.797 for a confidence interval 95% p> 0.05, this shows that there isn’t a significant difference between the values of waiting time in and the employment status.

For the employment, an average of 59.42 days was evaluated for the women with sickness/disability category, followed by the pensioner group with an average value of 43.48. The lowest average waiting times is for the group of active working women with a value of 35.71 days, determining a higher standard deviation in women with sickness/disability with a value of 76,950 with

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23 respect to the mean. In other studies, were not found significant difference according employment status [24] in comparison with our study where women with job have significantly lower WTs (35.71 days) comparing it with the group with women with disabilities or pensioners (59.42 and 43.48 respectively).

Financial situation. In the Kolmogorov-Smirnov test as the level of significance is less than 0.05, we evaluate that there is

no adjustment to the normality, that allow us to evaluate the alternative non-parametric Kruskal–Wallis H distribution test.

The level of significance is greater than 0.05 (p = 0.917) for a 95% CI we accept that financial situation does not differ too much correlating it with the variable time between diagnosis and treatment.

Surprisingly, in our study the high (43.9 days) or very high (52.4 days) income level patients were exposed to longer waiting time for surgery (p>0.05) in comparison with the poor affluence group (47.8 days). This is somewhat skewed by the small number of subjects in the group of women that conceive its financial situation as “very good”, only 38 versus 120 and 146 of the women that consider its financial situation “good” or “poor” respectively, valuing that the standard deviation is very high in the high income, with a dispersion of 80.068.

As we see, in our study, similar waiting times (p>0.05) are found in the different groups of economical status, having for those women with “very good” economical situation a delay of approximately 5 days in comparison with group of low/poor economic situation. Our results differ from other studies [27] where women with no income and those who earned less had significantly longer waiting time than those who earned more.

5.3 Clinical characteristics of the study population and its correlation with the diagnosis to treatment waiting times

In the table 5 is shown a descriptive analysis of the clinical characteristics for the newly diagnosed women with breast cancer in Lithuania during 2011.

Type of surgery. The type of the surgery was related with the waiting time. The breast conservative surgery (BCS) was

applied to 59.2% of all cases. In comparison, mastectomy was provided for 34.9% of women with breast cancer. During the selection of this variable 20 of these women were not included because they were treated by non-surgical methods.

Stage of breast cancer. We divided the woman between into the two groups - those who had a histological noninvasive or

early stage cancer (0+1+2) and those who had a late stage cancer (3+4). For a sample size of 307 breast cancer patients with 31 lost women, we assessed that the stage group highest frequency is the group noninvasive/early stage with a percentage near to 70% (69.8%) in comparison with a late stage group with a percentage of 21%.

Metastasis status. For the last clinical variable studied, in a clear 96.4% were not diagnosed with metastasis in comparison

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Table 5: Clinical characteristics of the studied patients (n=338)

Clinical characteristic Distribution of subjects N (%) Number of responders Type of surgery 318 - Mastectomy - BCS 118 (34.9%) 200 (59.2%)

Stage of breast cancer 307

- Early stage (0+1+2) - Late stage (3+4) 236 (69.8%) 71 (21%) Metastasis status 338 - No metastasis - Metastasis 326 (96.4%) 12 (3.6%)

In Table 6, a test of comparison of means is performed to assess the mean of the waiting times between diagnosis and surgical treatment in correlation with the stage group, presence of metastasis and type of surgery.

Type of surgery. Type of preplanned radical treatment (mastectomy or BCS) had an evident relation with the waiting time.

It was observed that patients were waiting for mastectomy was on average 64.52 days. In contrast, women treated with BCC were waiting for 35.75 days. This implies that women were waiting significantly longer (p=0.000) for mastectomy surgery than comparison BCS treatment. Such situation was demonstrated in several studies [40-42], where longer delays were associated with worsened prognoses, reduced survival rates and a higher incidence of mastectomy.

Stage of disease. Stage of the breast cancer also showed relation with the waiting time. Is characteristic to observe that

patients with a longer waiting time related with a more advanced stages with an average value with 62.5 days compared to an average of 42.9 days in an early stage. This implies that women with late stage were waiting significantly longer (p=0.02) than comparison with the ones in non-invasive/early stage. This could be attributed to the delay in time for surgery due to initiation of other kind of treatment (neoadjuvant chemotherapy) or the more precise studies requesting before surgery (MRI, PET..).

This is quite different comparing it with the results of 2 Canadian studies [47, 48] where the later stages of cancer had lower waiting times between diagnosis and surgery comparing it with the earlier stages.

Metastasis status. There is statistically significance between waiting time between diagnosis and surgery among the patients

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25 waiting time between diagnosis and treatment is about 45 days, but if we compare it with the waiting time in women with metastasis the waiting days is almost the double, with a value of 82 days. This could be due to what we mentioned above about later cancer staging.

Table 6: Distribution of mean waiting time between diagnosis to surgical treatment by clinical characteristics of patients (n=308)

Clinical variables Mean of waiting time (days) Standard deviation (SD) Distribution of subjects N (%) N (%) Number of responders p-value 1. Type of surgery 306 Mastectomy

Breast conservative surgery

64.52 35.75 7.043 3.172 113 193 36.9% 63.1% 0.00

2. Stage of breast cancer 287

0+1+2 3+4 42.99 62.53 3.773 8.419 229 58 79.8% 20.2% 0.02 3. Metastasis status 308 No metastasis Metastasis 45.27 82.27 3.349 24.603 297 11 96.4% 3.6% 0.04

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6. CONCLUSIONS

1. The average waiting time from histological diagnosis until surgical treatment for the newly diagnosed breast cancer women was 46.6 days (6.6 weeks or 1.5 months) in Lithuania during 2011.

2. Majority of patients (71.43%) were exposed for longer than the recommended waiting time by the EUSOMA.

3. In our study longer waiting time from diagnosis to surgical treatment was not significantly associated (p>0.05) with demographic characteristics such as the age of patient, rural or urban place of residence, despite some minor statistical differences were observed.

4. Waiting time was not significantly associated (p>0.05) also with analyzed socioeconomic characteristics of patients (lower level of education, lower level of income, not regular employment status).

5. The radical mastectomy was related with longer waiting time from diagnosis to treatment in comparison with the breast conservative surgery (p<0.05). Later stage of breast cancer and the presence of metastasis was also associated with the longer waiting time between diagnosis and treatment (p<0.05).

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7. PRACTICAL RECOMMENDATIONS

1. General practitioners and doctors of secondary and tertiary level should be introduced with standards of cancer patient care recommended by the EUSOMA.

2. The creation of a rapid oncological breast cancer diagnosis centers should be one of the priorities in the improvement of the breast control’s effectiveness in order to reduce the observed inequalities in access to treatment in different demographic, socioeconomical and clinical groups

3. Increasing of cancer awareness among women should be implementing through the national programs focusing on health literacy of population and favoring breast self-examination and participation in the breast cancer-screening program. 4. More research is needed to fully understand the role of clinical practices, and access to and/or utilization of cancer care

services in order to improve breast cancer survival and decrease survival differences by demographic and socioeconomic groups.

5. These results suggest that waiting times from diagnosis to treatment could be a good indicator and could reveal inequalities in cancer care access.

6. Measuring and analyzing waiting time from diagnosis to treatment by different demographic, socioeconomical and clinical groups could lead to improvement of quality of cancer screening services by implementing better collaboration between service providers, including outpatient and inpatient facilities.

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