MEDICINE AND ALZHEIMER’S DISEASE (MEDALZ) (STUDY 1 AND 4)

4.1.1 Study population and design

Study 1 of this thesis is based on the MEDALZ-2005 population, which is a case control study and includes all community-dwelling women with a clinically verified AD diagnosis, residing in Finland on 31^st December 2005 (n=19,043). Cases were identified from the Special Reimbursement Register and an age, gender, and region of residence matched control was assigned to each case (n of matched case control pairs= 19,043).

The age range of women was 42-101 years and the follow-up period was from 1986-2005.

Study 4 (MEDALZ) has many similarities to MEDALZ-2005, but it includes those who received a clinically verified AD diagnosis between 2005-2011, and one to four age-, sex- and region of residence- matched comparison persons for each individual with AD (n of cases=70,719, n of controls 282,862, N =353,581). The age range of the cohort was 34-105 years (mean 80.1 (SD 7.1) years) and 246,117 (65.2%) of the sample were women. Our study comprises of 230,580 women (n of AD cases=46,117 and n of controls= 184,463) with a follow-up period from 1995-2011.

Controls were identified from the register that contains all residents of Finland who are entitled to benefits from the Social Insurance Institution, i.e. all citizens and residents living in Finland for at least two years. Each resident of Finland is assigned a unique social security number which was used to link the participant’s data to national Hospital Discharge Register.

4.1.2 Exposure data

For study 1, data on bilateral oophorectomy, hysterectomies, and hysterectomy in combination with bilateral oophorectomy during 1986-2005 was obtained from the National Hospital Discharge Register. Surgeries occurring after AD diagnosis were not taken into account. From 1996-2005, we used Nordic Medico-Statistical Committee’s Classification of Surgical Procedures (NOMESCO) codes for operations [NOMESCO-2010]. During 1986-1995, we used the corresponding codes from the Finnish Classification system. As a malignant neoplasm is one of the indications for these surgeries, we analyzed the association of gynecological surgeries and AD separately in women with and without history of malignant neoplasm of cervix uteri, corpus uteri, uterus, or ovary with the following codes from the International Classification of Disease (ICD-10 codes C53-C56 and C57.0 and the corresponding ICD-9 and ICD-8 codes). Data on these diagnoses was taken from the hospital discharge register (years 1986-2005) (Figure 4).

Figure 4: Prevalence of surgery (%) among cases and controls in the MEDALZ-2005 study from 1986-2005 (study 1)

Data on HT use from 1995-2005 for study 1 and from 1995-2011 for study 4 were extracted from the National Prescription Register which contains information about the drugs dispensed at pharmacies to all Finnish residents living in non-institutionalized settings since 1995 and is maintained by the Social Insurance Institution. The following Anatomical Therapeutic Chemical (ATC) codes were used to identify the drugs: G03C (estrogen), GO3D (progestogen), G03F (estrogen and progestogen in combination), and G03X (other sex hormones and modulators of genital system) (Figure 5). Only systemic HT (oral or transdermal) was taken into account. Based on the register records, we were able to categorize HT use into (never users, users 1-5 yrs, users for 6-9 yrs and users for 10-11 yrs) for study 1 and (never users, users for 1-5 yrs, 6-9 yr users and users for >10 yrs) for study 4. Type and mode of HT use were available for study 4 but not for study 1.

In both studies, the purchase data from prescription register was modelled to periods of use by a decision procedure that included each person’s purchase history for each ATC code, processed in a chronological order. The method constructs exposure time-periods and estimates the dose used during that period by considering the purchased amount in defined daily doses. This method takes into account stockpiling of drugs, personal purchasing patterns i.e. regularity of the purchases, and periods of hospital or nursing home care where drug use is not recorded in the prescription register (Tanskanen 2015).

3,69%

4,24%

6,69%

7,49%

3,21%

3,69%

AD cases (n=19,043) Controls (n= 19,043)

Bilateral oophorectomy Hysterectomy Hysterectomy with bilateral oophorectmy

Figure 5: Use of HT (%) among cases and controls in MEDALZ population (study 4) 4.1.3 Outcome data

Persons with AD in both studies were identified from the Finnish Special Reimbursement Register maintained by the Social Insurance Institution. The Special Reimbursement Register contains records of all persons who are eligible for higher reimbursement due to certain chronic diseases; this includes AD. To be eligible for reimbursement, the disease must be diagnosed according to specific criteria and a diagnosis statement must be submitted to the Social Insurance Institution by a physician. The specific criteria for a verified AD diagnosis are 1) symptoms consistent with mild or moderate AD, 2) a decrease in social capacity over a period of at least 3 months, 3) a computer tomography/magnetic resonance imaging scan, 4) exclusion of possible alternative diagnoses, and 5) confirmation of the diagnosis by a registered neurologist or geriatrician. Diagnosis of probable AD was based on the NINCDS-ADRDA and DSM-IV criteria.

4.1.4 Covariables

A co-morbidity score was calculated for both studies using the Charlson Comorbidity Index as a reference. For study 1, information on chronic diseases was taken from the Special Reimbursement Register. The modified Comorbidity score for study 1 was calculated using the following diseases with corresponding scores; heart failure, coronary artery disease, type 1 or 2 diabetes, chronic asthma or chronic obstructive pulmonary disease, disseminated connective tissue diseases, rheumatoid arthritis and other comparable conditions (score of 1); uremia requiring dialysis, severe anemia in connection with chronic renal failure, leukemia, other malignant diseases of blood and bone marrow including malignant diseases of the lymphatic system, and all cancers (score of 2). Due to the skewed distribution, the score was categorized to “0”, “1”, “2”, and “3” or more and modeled as an ordinal variable.

For study 4, data on co-morbidities from 1972 until 5 years before the AD diagnosis of index case were extracted from the Hospital Discharge Register. To avoid collinearity,

19,99%

18,38%

11,66%

10,60%

AD cases (n= 46,117) Controls (n= 184,463)

Any estrogen use Any progestogen use

a composite score was derived for those predictors that were associated with the risk of AD in this cohort as follows: cancer, pancreatic insufficiency and renal insufficiency were scored as -1; peripheral vascular disease, asthma/chronic obstructive pulmonary disease, diabetes, cardiac arrhythmia, mental and behavioral disorders, ischemic heart disease, stroke, hemiplegic, anemia, and liver disease as 1; alcohol abuse, psychosis, fluid and electrolyte disorders, and weight loss as 2; and epilepsy as 3. The scores were summed together to derive an overall index, with higher values indicating higher risk of AD.

Socioeconomic status was estimated from the censuses maintained by Statistics Finland based on occupational social class and was available only for study 4. The data was collected at 5 year intervals starting from 1970 until 2000, and annually from 2004 onwards. Based on the associations between original socioeconomic categories and AD, socioeconomic status was categorized into 6 classes. For each individual, the highest class from 1970 until 5 years before AD diagnosis was used (Tolppanen et al., 2016).

4.2 KUOPIO OSTEOPOROSIS RISK FACTORS AND PREVENTION