1.- Overview:

Goal: To describe the occurrence of a disease (Fractures) in determined population (Osteoporosis patients) in a period of time (In 2022)

The incidence rate of fracture will be calculated as the number of new (first-ever) fracture events over the total person-time at risk in the reference population. Person-time at risk is defined for each patient as the time they are at risk of experiencing a first-ever fracture in 2022.

Inclusion/exclusion criteria rules:

Inclusion criteria

  • A minimum of 365 days of database history is required to identify prevalent patients.

  • The start of the time at risk will be defined as the latest of the following dates:

    • 1 st January 2022 (study start)
    • Start of registration with the database + 365 days (minimum required database history)

  • The end of time at risk will be defined as the earliest of the following dates:

    • 31 st December 2022 (study end)
    • End of registration with the database
    • First occurrence of a fracture event in 2022

Exclusion criteria

  • Patients that are not registered in the database in 2022 will not be included in the analysis.
  • Patients with a fracture event recorded at any time before the study period (i.e. prevalent patients) will not be included in the analysis.

The following formula will be used to calculate the incidence rate of fracture:

$IncidenceRate= \(\frac{numberIncidentPatients}{TotalPersonYearsAtRisk}\) *100000 $

Where the total person-years at risk will be the sum of all patients’ time at risk (in years) as defined above. Incident patients are defined as those patients experiencing a first-ever fracture in 2022. Incidence rate will be reported by gender and in total.

2. Steps for analysis (end-to-end)


1.- Load libraries and main sources

2.- Declare Functions (for tableshells)

3.- Pre-processing Data Quality and Data transformations 1

4.- Data transformations 2 (connect tables and flags to filter by)

5 .- Filtering table to get the Target sample population for this Study Analysis

6.- Generate table shells


3.-Results:

Female Male Overall
Person-years at risk 15.06913 15.06913 15.06913
Patients with a first-ever fracture 61.00000 49.00000 110.00000
Incidence rate 404801.05378 325168.05959 729969.11337

Table 1.- Incidence rate per 100.000 person-years. NOTE: Rates can only be expressed as new cases per unit of person-time.


STEP EXTRA.A - Generate plots to explain incidence rate

## 288 missing observations were removed.

Figure 1.- The distribution of the weekly incidence per gender seems to be “negatively skewed”. Seems to be a pattern of incidence of Fractures along time . This can be modeled with a log-linear regression function.


STEP EXTRA.B - Prediction model curves with log-linear regression function.

## Warning in fit(incidence_fracture2022_gender_object_optA): 20 dates with
## incidence of 0 ignored for fitting
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.

Figure 2. Weekly Incidence rate Log Linear Regression Fit


Female Male
Growth rate (r) 0.0015502 0.0033026
  • CI Lower (2.5%)
-0.0006824 -0.0020874
  • CI Upper (97.5%)
0.0037828 0.0086926
Doubling (doubling time in days) 447.1371761 209.8780530
  • CI Lower (2.5%)
183.2361640 79.7395761
  • CI Upper (97.5%)
-1015.7051404 -332.0625396

Table 2. Log Linear Regression Fit: We can see the model shows a small growth rate in both genders. Further research with more samples will be required.