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C. Montuclard1, V. Jooste1, V. Quipourt2, S. Marilier2, J. Faivre1, C. Lepage1, A.M. Bouvier1


1. Registre Bourguignon des Cancers Digestifs, Inserm U866 and CIC-EC, Dijon ; Université de Bourgogne; CHU Dijon; 2.  Unité de Coordination en Oncogériatrie en Bourgogne (UCOGB), Hôpital de jour gériatrique, Centre de Champmaillot, CHU Dijon.

Corresponding Author: Anne-Marie Bouvier, Registre Bourguignon des Cancers Digestifs [INSERM U866], Faculté de Médecine, BP 87 900 21079 Dijon Cedex, France. Tel : (+33) 3 80 39 33 40  Fax : (+33) 3 80 66 82 51, E-mail : anne-marie.bouvier@u-bourgogne.fr



Background/Objectives: Data on the time between colorectal cancer diagnosis and treatment in real-life practice for elderly patients are scarce. We measured times from diagnosis to first-course therapy in elderly patients with colon and rectal cancers. Design: The study was carried out on the population-based Burgundy Digestive Cancer Registry (France). Setting: Therapeutic delays were described by medians and interquartile ranges and compared by the Kruskal-Wallis rank test. Factors associated with changes in therapeutic delay were identified using a multivariate Cox model. Participants: The analysis was carried out on 2,884 patients aged 60 years and over with colorectal adenocarcinoma diagnosed between 2005 and 2011. Measurements and Results: The median therapeutic delay for colon cancer was 25 days in patients aged 60 to 69 years and 24 days for those aged 70-79 years. The delay fell significantly to 19 days in patients aged 80 and over (p<0.001). The median therapeutic delay for rectal cancer did not vary according to age group (respectively 39, 38 and 33 days). For colon cancer, a Charlson comorbidity score=0, in all age groups, and private care for patients under 80 years, significantly shortened the therapeutic delay. It was significantly longer during the period [2008-2011] only in patients under 80 (HR: 0.89 [0.81 – 0.99] p=0.037). For rectal cancer, only advanced stage (HR advanced vs II: 1.39 [1.04-1.86], p=0.025) shortened the therapeutic delay in patients under 80, while private care shortened therapeutic delay only in patients over 80 (HR private vs public: 1.66 [1.00-2.74], p=0.049). Conclusion: This study highlights that differences in therapeutic delay for the elderly increased over time for colon and rectal cancer. The therapeutic delay did not differ much between the 60-69 and the 70-79 years age groups, whereas it was shorter for patients aged 80 and over.

Key words: Colorectal cancer, elderly, quality of life, registry, adjuvant treatments.

Abbreviations:  HR: hazard ratio, CI: confidence interval.



In France, colorectal cancer is the third most common cancer with an annual incidence of 40,000 (1) new cases. The ageing of the population and the rise in life expectancy, as well as the increasing incidence of colorectal cancer, will lead to a growing number of affected patients. Social inequalities in healthcare have been identified in every industrialized country whatever the amount of money the government spends on the organization of the health system. In the second and third ‘Cancer Plans’ launched in France, the French authorities established as a national priority the reduction of inequalities with regard to the management of cancers. Reasons for disparities in the management of cancer are multiple and complex. The age of patients is an established factor associated with disparities in the management of colorectal cancer (2). A number of mechanisms lie at the root of these disparities and can intervene at every step of the management, from the pre-diagnostic to the post-therapeutic phase. One of the factors that may determine the care of patients and the prognosis of the disease is the therapeutic delay. Recommendations concerning the therapeutic delay are scarce in Europe. Only the United Kingdom and Denmark produced guidelines recommending a limited delay between diagnosis and treatment. The precise measurement of the disparities that can exist between various groups of patients concerning the therapeutic delay requires data representative of the general population. In this context, cancer registries are a source of extremely useful data. The aim of this study was to describe the therapeutic delay in patients with colorectal cancer according to their age, and to identify epidemiological characteristics associated with disparities in this delay using a population-based digestive cancer registry.


Materials and methods

Study population

A population-based cancer registry records all digestive cancers in two French administrative areas in Burgundy: Côte-d’Or and Saone-et-Loire (1,064,000 inhabitants according to the 2011 census). Information is regularly obtained from pathologists in public and private practice, public hospitals (university hospitals including the cancer center and general hospitals), and private physicians: gastroenterologists, surgeons, oncologists, radiotherapists, general practitioners, hospital administrative databases, and the National Health System database and death certificates. No case is recorded through death certificates alone, but these are used as an identification source. Because of the multiplicity of medical and administrative information sources, it was assumed that nearly all newly diagnosed cancers had been registered. The quality of the data collection is evaluated every 4 years by the Institut National de la Santé et de la Recherche Médicale (INSERM), the Institut de Veille Sanitaire (InVS) and the Institut National du Cancer (INCa).Cancers were classified according to the International Classification of Diseases, 10th revision (3). Therapeutic delay was defined as the time between date of diagnosis and first oncologic treatment performed (surgery, radiotherapy or chemotherapy).
Overall 3,679 invasive colorectal adenocarcinomas were registered between 2005 and 2011 in patients aged 60 years and over. In case of two synchronous colorectal cancers, the shortest therapeutic delay was taken into account for the analyses. To avoid including patients with an irrelevant therapeutic delay, we excluded patients with synchronous non-colorectal cancer, patients who underwent emergency surgery (obstruction or perforation), patients treated by endoscopic resection during the diagnostic colonoscopy, patients with fortuitous diagnosis during a surgery for another reason, and patients not treated. A total of 774 patients were excluded. The therapeutic delay was unknown for 21 patients. Finally, 2,884 patients were included (79% cases with colon cancer and 21% with rectal cancer).

Data collection

The Digestive cancer registry contains key information routinely collected regarding patients’ characteristics (sex, age, place of residence, comorbidities, health care facilities), the tumor (stage at diagnosis), and treatment (date and nature of treatment including surgery, chemotherapy and radiotherapy). Patients were divided into three age groups: age 60 to 69, 70 to 79 and 80 and above. The period of diagnosis was divided into two groups, [2005-2007] and [2008-2011]. Cancer stage at the time of diagnosis was classified according to the TNM classification (4). Advanced cancer was defined by cancer stage IV and non-metastatic/ non-resected cancer. The place of residence was categorized according to the classification established by the French National Statistics and Economic Studies Institute (INSEE) into urban and rural areas. The date of diagnosis was generally defined by the date of the colonoscopy. When a colonoscopy had not been performed before treatment, the date of diagnosis was the date of the first positive imaging (CT-scan or barium enema). Comorbidities at the time of diagnosis were listed using the Charlson index (5). Individuals were then assigned to a group according to their index: 0, 1 or >1. The healthcare delivery pattern was classified into public hospitals (including university hospitals, general hospitals and cancer therapy centers), private hospital and mixed places of treatment (receiving care in both public and private hospitals).

Statistical analysis

The characteristics of the cohort were described using percentages. The therapeutic delay was calculated in days and was described by medians and inter quartile intervals (IQI). Medians were compared between different groups by Kruskal-Wallis tests in univariate analysis. Multivariate Cox proportional hazards models were used separately for colon and rectal cancer cases in order to determine what factors were associated with a greater probability of quick access to treatment. As radiotherapy or chemotherapy were very rare as first treatment for colon cancer, this variable was only analyzed for rectal cancer.


Table 1 shows the descriptive data for the whole population according to cancer location. The distributions of the main variables did not differ by age group between colon and rectal location. For both colon and rectal cancers, there was a greater proportion of women in patients over 80 than in younger patients. In patients over 80 with colon cancer, the proportion of patients managed in public facilities was higher than the proportion of patients managed in private facilities (53% vs. 34%) whereas patients under 80 were more often managed in private facilities. Colon cancer was diagnosed in a context of sub-occlusion for 5% and 6% of patients aged 60 to 69 and 70-79, respectively, and for 9% of those over 80.
For rectal cancer, the proportion of patients receiving chemo or radiotherapy at first treatment was lower in the oldest age group than in the youngest (54% vs. 69%). Overall, 45% of patients aged over 80 had a Charlson score=0. This proportion for the 60-69 year-olds was 59% for colon cancer and 72% for rectal cancer.


Table 1 Characteristics of the population according to location of the cancer

Unknown: *45 cases, ** 9 cases.  CT: chemotherapy, RT: radiotherapy, # Including patients with visceral metastasis and non-resected tumours without evidence of visceral metastasis


The median delays between diagnosis and treatment and their variations according to age groups and patients’ characteristics for colon and rectal cancers were assessed. The median therapeutic delay was 25 days 95%CI [13-41] for the whole population. Delays were shorter for colon cancer (22 days 95%CI [12-36]) than for rectal cancer (37 days 95%CI [24-55]).

Colon cancer

The overall median therapeutic delay for colon cancer was 25 days 95%CI [14-39] in patients aged 60 to 69 years and 24 days 95%CI [13-39] for those aged 70-79 years.  It decreased to 19 days 95%CI [8-32] in patients aged 80 and over (p<0.001). Therapeutic delays were significantly shorter in patients over 80 years compared with those aged less than 79 years for all studied variables except for patients managed in public and private facilities (Table 2). Neither sex nor place of residence was significantly associated with shorter access to treatment in the multivariate Cox analysis (Table 3). A Charlson comorbidity score of zero was significantly associated with a shorter therapeutic delay in patients in all age groups. Care in a private facility was associated with a shorter therapeutic delay only in patients under 80 (HR: 1.16, [1.03-1.31], p=0.017). The delay was significantly longer during the most recent time period only in patients under 80 (HR: 0.89, [0.81-0.99], p=0.037) and for stage I for patients in all age groups.


Table 2 Therapeutic delay (days) for colon cancer by age group

IQ: inter quartile interval,  # Including patients with visceral metastasis and non-resected tumours without evidence of visceral metastasis


Table 3 Factors associated with quicker access to treatment after diagnosis of colon cancer according to age (Cox proportional hazards model)

HR>1means quicker access to treatment, # Including patients with visceral metastasis and non-resected tumours without evidence of visceral metastasis


Rectal cancer

The overall median therapeutic delay for rectal cancer did not significantly vary by age group. It was 39 days [20-56] in patients aged 60 to 69 years, 38 days [23-56] for those aged 70-79 years and 33 days [20-55] for those aged ≥80 years. Therapeutic delays were significantly shorter in patients over 80 years than in younger patients for patients with an advanced stage cancer, those living in rural areas, those managed in private health care facilities and those with surgery as the first treatment (Table 4). After adjustment for all concerned variables, place of residence and first surgical treatment were no longer associated with a shorter therapeutic delay for all patients. Private facilities (HR private vs public: 1.66 [1.00-2.74], p=0.049) were significantly associated with a shorter therapeutic delay for patients over 80 years (Table 5).


Table 4 Therapeutic delay (days) for rectal cancer by age group

IQ: inter quartile interval,  CT: chemotherapy, RT: radiotherapy, #Including patients with visceral metastasis and non-resected tumours without evidence of visceral metastasis


Table 5 Factors associated with quicker access to treatment after diagnosis of rectal cancer according to age (Cox proportional hazards model)

CT: chemotherapy, RT: radiotherapy , #Including patients with visceral metastasis and non-resected tumours without evidence of visceral metastasis. HR>1means quicker access to treatment


Our study examines real-life disparities in care related to delay between diagnosis and treatment in the elderly with colon and rectal cancers. The strength of this study is that it relies on a large population-based sample, allowing separate analyses for colon and rectal cancers. The therapeutic delay did not differ much between the 60-69 and the 70-79 years age groups, whereas it was shorter for patients aged 80 and over. The therapeutic delay increased with time period for patients younger than 80 years old with colon cancer whereas it did not vary for the oldest patients and for patients with rectal cancer. For colon cancer, sub-occlusion at diagnosis was almost twice as common in the oldest age group than in the youngest, which may partly explain the shorter therapeutic delay for the oldest patients. Patients managed in private facilities and presenting with advanced tumors were more likely to have a short therapeutic delay, and comorbidities did not strongly interact with this delay.
Colorectal cancer is frequently encountered in the elderly: 60 to 70% of cases occur in subjects aged 65 or older, and around 45% in those over the age of 75 (6). The improvement in life expectancy plus the increased size of the elderly population have led to a growing number of patients with the disease. Therefore, the care of elderly patients with colorectal cancer is a challenge. Measuring the inequality of treatment in patients with carcinoma is a major concern for the French health authorities, as underlined by successive Cancer Plans established in France since 2003. Disparities in the management of cancer in the elderly are multiple and complex; they can concern patients’ geographical, social or economic environment, and specific approaches are needed to reduce them. No association has been clearly established between therapeutic delay and all-cause death in colon and rectal cancer (7). This meta-analysis by Ramos et al. failed to demonstrate any association between therapeutic delay and the colorectal cancer stage. Data from the SEER program suggested that the shortest delay (<1 week) was associated with a higher risk of all-cause death than was the case with longer delays in colon cancer, whereas it had no impact on colon and rectal cancer-specific death (8). Nevertheless, in addition to the evident psychosocial stress for patients awaiting treatment, therapeutic delay among elderly patients may be a valuable indicator of health care quality.
Unlike other countries, France has the theoretical advantage of a relatively homogeneous population, all of whom have the same national health insurance access to care throughout their lives. Nevertheless, the waiting time from diagnosis to treatment may vary among the elderly. The precise measurement of the disparities that can exist between various groups of patients concerning these delays requires the recording of representative data of the general population. Due to unavoidable selection bias, hospital-based data cannot be considered representative. Population-based registries allow the collection of exhaustive data from all sectors of care in well-defined geographical areas.
There are few studies concerning the therapeutic delay for colorectal cancer in the general population. In our study, the median therapeutic delay was 22 days for colon cancer and 37 days for rectal cancer. A Canadian population-based study showed shorter median therapeutic delays: 12 days for the treatment of colorectal cancer in 2005 (9). In a recent population-based study in the USA, median treatment delays were 13 days for colon and 16 days for rectal cancer8. Other studies demonstrated longer treatment delays for rectal than for colon cancer. However, it is difficult to compare estimates of delay across studies due to differing definitions of delay (10). No previous study has been specifically dedicated to elderly patients and guidelines for maximum acceptable delays are still vague. For example, United Kingdom guidelines state that patients with cancer should have treatment initiated within 2 months of referral by general practitioners (11-13). In Denmark, the recommended maximum interval between referral and the work-up for colorectal cancer is 14 days, with the beginning of treatment within an additional 14 days (14). In France, there are no recommendations concerning therapeutic delays. Our study emphasizes that patterns of care concerning therapeutic delay did not much differ for patients less than 80 whereas it was shorter for those over 80 years of age. The reasons for this variability are numerous and the difference can be partly explained by different baseline characteristics of elderly patients and by changes in access or the physicians’ treatment decisions. The reason for the increase in delays over time for patients less than 80 years is unclear as it concerned only colon cancer.
The increase may be partly related to longer access to the preoperative work-up or to a more complete assessment over time. Delays are likely to continue increasing given the continuing growth of the elderly population and the increasing use of complex, multimodal treatments (15). Neoadjuvant treatments are used for rectal cancer and require medical oncology referrals (radiation oncologists, surgeons and chemotherapists), which could lengthen the delay to the first treatment. As previously published, patients with early TNM stage I cancer had longer therapeutic delays than patients with more advanced cancers15. The reasons remain unclear.  
Elderly patients managed in private facilities showed shorter therapeutic delays. In France, cancers are managed by a highly decentralized health care system, with many treatment facilities and many participants. The supply of care is heterogeneous and certain management disparities may be associated with the organization of the health care system or with the individual characteristics of the patients.
A recent publication has showed that the concordance between the therapies proposed during the tumor board or after the geriatric oncology consultation and the treatment actually given was satisfactory. Currently, the geriatric oncology consultation is performed quickly and does not influence the therapeutic delay (16) .
The main limit of this study is obviously its retrospective observational status, which prevented us from including relevant data, particularly on patients’ socioeconomic level. It would have been interesting to measure how deprivation may have influenced cancer management at the population level. Information on nutrition status would also have been interesting; malnutrition is frequent and may be associated with longer hospital stays, worse outcome, impaired quality of life and performance status (17). The relatively low number of rectal cancer cases may also have led us to miss or under or overestimate some statistically relevant items.
In conclusion, this study highlights that therapeutic delays are shorter for patients over 80 years than for younger patients. Factors affecting this delay are scarce but similar in both age groups. If the range of days of therapeutic delay is not widely extended, the effect of variations in delays on patients’ outcomes, such as recurrences or death, should nevertheless be explored in future research.


Conflict of interest: None

Ethical standards: The project comply with the current laws of the country.

Sponsor’s Role: The sponsors of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Disclaimer: None of the authors has any conflicts of interest to declare regarding this study.

Funding sources: French Institut national du cancer (INCa), Conseil Régional.



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I. Goldshtein1,3, J. Chandler2, V. Shalev1,3, S. Ish –Shalom4, A.M. Nguyen2, V. Rouach5, G. Chodick1,3


1. Epidemiology and database research unit, Maccabi Healthcare Services, Tel Aviv, Israel; 2. Department of Epidemiology, Merck and Co, Inc, North Wales, PA; 3. Tel Aviv University, Israel; 4. Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel; 5. Institute of Hypertension, Metabolism, and Endocrinology, Tel Aviv Souraski Medical Center, Tel Aviv, Israel

Corresponding Author: Inbal Goldshtein, Maccabi Healthcare Services, 27 Ha’Mered Street Tel Aviv 68125 Israel, Tel: 972 3 7952616   Fax: 972 73 2132831, E-mail: goldst_in@mac.org.il



Background: Osteoporosis is a growing public health concern due to its rising prevalence and excess morbidity and mortality. Automated patient registries have gained great importance in health and disease management of major chronic diseases, but are rarely used in osteoporosis. Objectives: To construct an automated, population-based registry of osteoporosis. Setting: The electronic medical records and pharmacy databases of a 2 million member health organization in Israel (Maccabi Healthcare Services). Methods:  Included in the registry were adults who were diagnosed with osteoporosis diagnosis, had major osteoporotic fractures, or purchased relevant medications, between 2000 and 2013. In addition, we included patients with low bone density as extracted from over 140,000 measurements reports, using an automated optical character recognition (OCR) system. Two-thirds of the cases were validated by more than one inclusion criterion. Results:  A total of 118,141 osteoporosis patients were identified.  The point prevalence of osteoporosis among members aged 50 or above in 2013 was 19%. The mean age at registry entry was 62 (SD=12) and 66 (SD=14) years for females and males, respectively. The highest annual risk of developing osteoporosis (27 per 1000) was recorded among females aged 65-75. In 28% of the patients, there was no indication of treatment with osteoporosis therapy. Conclusions: To the best of our knowledge, this is one of the first real-world automated registries of osteoporosis. Similar registries may provide valuable data for real-time monitoring of trends, quality of care, and outcome research in osteoporosis and its complications. 

Key words: Osteoporosis, registry, prevalence.



With a growing elderly population and a prevalence of over 200 million people worldwide (1), the global epidemic of osteoporosis (OP) poses a serious public health concern. The major medical, social, and economic consequences of osteoporosis are due to osteoporotic fractures resulting in disability (2-4) and excess mortality (5). In white populations, the lifetime risk of fragility fracture is approximately 50% in females and 20% in males (6). 

In addition to fractures, other manifestations of osteoporosis such as low bone mineral density (BMD) and vertebral deformities have been strongly associated with increased risk of death from stroke (7), coronary heart diseases (8) and pulmonary diseases (9).

Considerable variations were observed between countries with regards to OP fracture rates (10-12), warranting the need for local estimations. The reason for such variations may lie in genetic factors or environmental factors, as well as differences in measurement and reporting systems, or differences in case-finding approach. Self-report survey studies, insurance claims-data, and hospital-based studies have shown to underestimate fracture risks (13-15). 

Israel has a social public health care system and developed sources of data that allow the population-based analyses on the burden of chronic diseases that can be generalized to other western-like populations (16-19). 

The available data (20-23) on the epidemiology of osteoporosis and mortality among patients with OP  fractures in Israel are partial and outdated and thus may not reflect important changes in recent years such as increased life expectancy and introduction of new anti-osteoporotic treatments.

The objective of the present study was to establish a registry of osteoporosis patients using automated collection of individual-level information on important characteristics[24] such as demography, co-morbid conditions, medication use, laboratory tests, and bone densitometry measurements. Specifically, the registry was analyzed to assess the current age-and-sex specific prevalence of osteoporosis, history of OP fractures, and a retrospective assessment of all-cause mortality among patients with OP fractures. 


Materials and methods


This study utilized the longitudinal databases of Maccabi Healthcare Services (MHS), the second largest sick fund in Israel, ensuring 25% of the population with a nationwide and representative distribution. These databases are derived from electronic medical records (EMRs) of a stable population of over 2 million ensured members. Israel’s sick funds provide a uniform legally defined basket of services to which every citizen is entitled as a member of one of four nationwide health funds that are financed by government via age-related capitation payments (90% of total), patient charges and other income (10%).  Citizens are free to choose and move between health funds, which are not exclusive and must accept all applicants for memberships. .

BMD measurements were collected from the datasets of a single chain of medical centers (“Assuta Health Systems”), where approximately 86% of the dual-energy X-ray absorptiometry (DXA) scans in MHS are performed.  All DXA scans in these clinics are conducted using a standardized model of GE- lunar prodigy scanner. 

Study population

Eligible for the study registry were all MHS members aged 18 or above with any of the following inclusion criteria: a physician diagnosis of osteoporosis (according to the International Classification of Diseases version 9 with clinical modifications (ICD-9-CM) codes: 733.0-733.03, 733.09, 733.7) , or osteopenia (ICD-9-CM code: 733.9) validated by any fracture one year before or after date of diagnosis, OP-specific therapy (defined by a dispensed medication prescription of any of the following: Bisphosphonates, Raloxifene, Strontium Ranelate, Teriparatide or Calcitonin), a minimum t-score of -2.5 or less , or a clinical diagnosis of a major osteoporotic fracture (MOF) or hip fracture surgery. MHS database does not include data on trauma type, except for fractures of road accidents, thus we could only partially distinguish between osteoporosis related fractures and high-impact trauma fractures. Thus, to ensure high specificity of the registry we considered only MOF for females aged 50 or above or in males aged 60 or above for independent inclusion criteria. MOF includes fractures commonly associated with osteoporosis: closed fractures of femur, vertebral, colles and proximal humerus, which were not listed in the database as associated with a car accident. Other closed fracture diagnoses may be related to osteoporosis but not considered specific enough and were used only for descriptive analysis. 

Excluded from the registry were patients with Paget’s disease (ICD-9-CM code 731.0, n=587) or multiple myeloma (203.0, n=631) as indicated in the EMR or hospital discharge, patients whose only qualifying registry entry criteria was fracture and either suffered from multiple fractures at the same date (n=640, most likely overwhelming trauma and not OP) or fractures due to metastatic cancer (n=107), and patients whose only qualifying registry entry criteria was pamidronic or zoledronic acid purchase and who were previously diagnosed with cancer (cancer is an alternative indication to these drugs in addition to OP, n=301).

Registry entry date was defined as the first medical event (diagnostic code, associated drug prescription, lab value or procedure) which is consistent with any of inclusion and all exclusion criteria. 

Co-morbid conditions were defined by MHS registries for chronic major diseases such as ischemic heart disease (25), diabetes (26) and hypertension. Renal impairment at follow up was defined by last eGFR measurement <=35 or patient in the MHS dialysis registry. Recent depression was defined as at least 6 purchases of SSRI in the last 2 years.

Socioeconomic status (SES) was defined by the 2008 national census (27) according to the poverty index of the member’s enumeration area, ranging between 1 (lowest) to 20 (highest). 

Study periods 

Follow up date was defined as the earliest of disenrollment from MHS, death, or December 31, 2013. 

Inclusion period: between Jan 1st 2000 and Dec 31st 2013. 

Statistical analysis 

Age and sex specific prevalence rates were determined for December 2013. 95% Confidence intervals for osteoporosis prevalence were calculated using the exact binomial (Pearson-Klopper) method using R statistical software (28). 

Age-and-sex standardized morbidity ratios (SMRs) with 95% confidence intervals were computed to compare between the OP registry and the general population of MHS.

We calculated OP incidence density rates during the study period after excluding members diagnosed with OP less than 3 years prior to first year of follow-up, as well as members with less than 5 years of continuous membership in Maccabi before diagnosis, to ensure selection of newly developed cases. For incident cases of osteoporosis (or MOF), only the time until cohort entry (or MOF diagnosis) contributed to the denominator of patient-years at risk.

We assessed primary incidence of MOF in MHS. Clear distinction between reports on incident events and follow-up of previous events is often difficult. High rates of surgery complications, delayed healing, recurrent complaints on past events[29], and the need for follow-up, may limit the accuracy of previous assessments of incidence. Thus we assessed only primary incidence, which cannot be compared to non-primary annual rates.

The study was approved by the Assuta hospital’s institutional review board.


A total of 118,141 eligible patients were identified for the registry, with approximately 6,000 incident cases annually (table 1). The mean duration of follow-up since first indication of osteoporosis was 7.9 years (SD=4.5). A total of 66% of the registry’s patients met two or more inclusion criteria, validating their OP status (Appendix A).  


Table 1 Demographics and comorbidities of osteoporosis patients with age and sex standardized morbidity ratios (SMR) compared to the general population in Maccabi healthcare services, December 2013

*Chronic obstructive pulmonary disease;  3. Socioeconomic status, ranging between 1 (lowest) to 20 (highest). See text for details;  4. Latest available measurement; 5. Systemic glucocorticoids; 6. Vitamin D deficiency was defined as <20 ng/ml. The calculation was out of non-missing data. 12% of the registry and 30% of the general population in Maccabi had missing vitamin D level.


Table 2 Age and sex specific prevalence rates per 1000 and 95% confidence intervals of osteoporosis in Maccabi healthcare services, Israel, 2013


Prevalence and incidence rates in MHS

The crude prevalence rates of osteoporosis among members aged 50 or above in MHS were 31.4% and 5.9% among females and males, respectively (table 2). Prevalence of MOF history increased exponentially with age reaching 30.1% in females and 11.8% in males at the age of 85 years or above (table 3).


Table 3 Age and sex specific prevalence rates (per 1000) of major osteoporotic fractures in Maccabi healthcare services, Israel, 2013


Figure 1a Age and sex specific incidence density rates and 95% confidence intervals of osteoporosis (per 1000 person years) in Maccabi healthcare services, 2003-20137

7. Error bars indicate 95% confidence intervals.


The highest incidence rate of OP was recorded at the age group of 65-74 and 55-64 among males and females, respectively (figure 1.a). The risk of MOF increases with age (figure 1.b). 

Demographics and comorbidities of OP registry patients

In 2013, the mean age of OP patients in MHS was 69.0 years old (SD=11.6), with females accounting for 85% of the registry (table 1). Compared with the age and sex adjusted general population of MHS, OP patients were more likely to have diagnosed history of COPD, Crohn’s disease, ulcerative colitis, and recent depression, and less likely to be obese, diabetic or have vitamin D insufficiency.


Figure 1b Annual age and sex specific incidence (per 1000 capita) of primary major osteoporotic fractures in Maccabi healthcare services, 2013


History of fractures in OP registry

Among OP patients with an indication of MOF history (29%), the most common fractures were hip among males (36.2%) and colle’s among females (37.3%). 

In addition, in 12% of the registry, we found an indication of non-MOF fractures that are likely to be related with osteoporosis (e.g. metatarsal, ribs, and ankle) which were not inclusion criteria for the registry. 

All-cause Mortality after OP fracture

Figure 1 depicts all-cause mortality rates within 1 year from date of MOF.  The highest mortality rates (23% in females and 32% in males) were observed among elderly patients (85 year or above) with a hip fracture.

Anti-osteoporosis therapy 

A total of 72% of the registry had at least one dispensation of osteoporosis medication ever. Among incident cases, treatment initiation rates were significantly higher (P<0.001) in females (75.3%) compared to males (62.1%). Only 24% of patients with hip fracture who were Anti-osteoporosis therapy naïve, initiated treatment after the fracture occurrence (22% were already treated before fracture event). This proportion is higher after vertebral fractures (38%) and lower after colles or humerus fractures (21%).


Figure 2 Age and sex specific all-cause mortality rates within 1 year from osteoporotic fracture event, Maccabi healthcare services, Israel, 2000-2013


Bone density measurements

Approximately 72% of the OP registry patients had an indication of performing a DXA scan. BMD values were electronically available for 52% of them (37% of the total registry).  Among the patients with t-scores of -2.5 or lower:  55% were <=-2.5 at femoral neck, 40% at spine and 5% total hip. In all but 3% (n=406) the femur neck indicated at least osteopenia. Mean values of DXA measurements at follow-up are given in table 1.



The present study described the establishment of an osteoporosis patient registry in a large and representative health organization in Israel, and the first population-based report of the epidemiology of this disease in the country. 

The results of the study reveal the immense burden of osteoporosis in Israel, with prevalence rates of 61% and 19% among females and males aged 75 or above. The observed OP prevalence was comparable to the findings of other large registries in Europe such as “BEST” (30) and “BoneEVA” (31). An Israeli survey (23) reported a lower prevalence (32% vs. 49% among females aged 65), possibly explained by the limitation of self-report data, as well as reduced awareness at that period (1999). The prevalence of diagnosed OP concords with a previous Israeli study (22) (14% vs. 13% among females aged 45-74, results not shown).  

In Israel, the remaining life expectancy of men and women at age 50 is approximately 31 and 35 years, respectively (CBS 2014). Therefore, according to our age-specific prevalence, the respective estimated OP-fracture lifetime risks in Israeli men and women are 6% and 30%,in accordance with previous international assessments (32, 33). Similar to previous large cohort studies (34, 35) our results indicate that while the absolute risk of hip fractures is two-fold higher among females, they account for a greater proportion of MOF among males. Similar to previous studies (36, 37), men were found to have a significantly poorer survival after hip fracture compared to women, although residual confounding by co-morbid conditions should be examined in future studies. 

In agreement with previous analyses among OP patients, we found increased SMRs for known risk markers such as COPD (38) and inflammatory bowel disease (IBD) (39) compared to the general population. Obesity and diabetes were decreased in the OP registry compared to the general population of MHS, with a BMI distribution similar to a recent large US cohort (40). 

This study has several major strengths such as a large and unselected population, a relatively long retrospective follow-up, standardized densitometry measurements, and automated collection of comprehensive data, including medical diagnosis, prescribed therapies, and lab tests. To our knowledge, this is the first registry of its kind in Israel, and one of the largest worldwide. We plan to update it periodically, identify new cases that meet the selection criteria in MHS and monitor outcomes.

Some limitation should be discussed, such as missing data on fracture circumstances, specifically to distinguish between OP related vs. high-impact trauma fractures. Our objective was high specificity of the registry, thus only typical/characteristic OP fractures were used as independent inclusion criteria, and multiple concurrent fractures were excluded (rarely OP-related, previously assessed as 2.5% of OP fractures (21)). In addition, pre-defined age cut-offs were used to identify MOF. The asymmetric age cut-offs between males and females (60+ vs. 50+ respectively) may yield somewhat lower sensitivity to detect males compared to females. Similarly to other retrospective population-based studies relying on clinical diagnoses, our data is likely to underestimate the rates of vertebral compression fractures (6), as these fractures are universally underdiagnosed.

Building a valid and efficient algorithm to detect patients for a central registry requires careful examination and assessment of the variety of different measures and definitions (41). The majority of the registry was validated by meeting at least 2 inclusion criteria. The remainder may be explained by low awareness for documentation and treatment initiation, non-compliance of patients, partial electronic availability of bone density values, or (less frequently) due to contra-indication of therapy. 

We believe this up-to-date registry can serve as a valuable resource for future studies in the field of osteoporosis and improve our understanding of the risks and prevention of osteoporosis. 


Funding: The study was funded by Merck and Co.

Conflict of interest: Sofia Ish-Shalom has received research grants and consulting, advisory board, lecture fees, and any combination of the three from Merck Sharp & Dohme, Eli Lilly, Enterabio, GlaxoSmithKline, and Novartis. Vanessa Rouach has received lecture fees from Eli Lilly, GlaxoSmithKline, and Novartis. Julie Chandler and Allison Martin Nguyen are employees of Merck and Co. Inbal Goldshtein, Varda Shalev and Gabriel Chodick declare that they have no conflict of interest.

Acknowledgments: We would like to thank Mrs. Racheli Katz and Mrs. Esma Herzel of Meaccbi Healthcare Services, for their considerable contribution to data collection. This work was performed in partial fulfillment of the requirements for a Ph.D. degree of Mrs. Inbal Goldshtein, Faculty of Management, Tel Aviv University, Israel.



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Appendix A Distribution of inclusion criteria in the Maccabi healthcare services osteoporosis registry