Predisposing factors for osteoporosis.

 

1. During case presentation at your clinic, you are reviewing four women with predisposing factors for osteoporosis. Which patient is least likely to be at risk for osteoporosis?

A. Nehineza, an overweight African American female with family history of uterine cancer
B. Cristina, a Hispanic woman living a sedentary life
C. Park-Gim-Ka, an underweight Asian woman with a history of tobacco use
D. Skylar, a Caucasian woman experiencing early onset of menopause.

2. Densitometry results are given as T-scores, which values would be considered as osteopenia?

3. After prompt analysis of your patient, you decide to institute treatment for osteoporosis. Which class medication is considered as the first-line treatment? Are there any considerations to be taken prior starting therapy? Which recommendations would you provide to the patient regarding this treatment?

Sample Solution

Based on the information provided, Skylar would be the least likely to be at risk for osteoporosis. Osteoporosis is a condition in which bones become weak and brittle due to a loss of bone density (Mayo Clinic, 2018). Risk factors for developing this disease can include early onset of menopause, as is the case with Skylar; however there are other more significant influencing factors that must also be taken into consideration.

Nehineza’s condition places her at an increased risk for developing osteoporosis due to her family history of uterine cancer as well as being overweight (Lau et al., 2016). Obesity has been linked with an increased risk of this condition due to its effect on hormones, specifically estrogen which helps regulate bone formation in women (Lau et al., 2016).

Cristina’s sedentary lifestyle could also potentially increase her chances of having low bone density since physical activity has been shown to help improve or maintain healthy levels (Mayo Clinic, 2018). Park-Gim-Ka may also face an elevated risk because she is underweight and smokes tobacco both of which have been found to adversely affect bone health (Bukar et al., 2017; Mayo Clinic, 2018).

Overall, these predisposing conditions should all be evaluated carefully when determining who is most likely to develop osteoporosis. There are many variables that influence someone’s chance of having low bone density so it is important not just identify them but understand how they interact with one another before making any conclusions.

Genes that have genetical variation encode enzymes which metobolize drug, drug transporters, or drug targets. Variation in genes that can predict dose and safety of treatment for different types of cancer patient can have harmful influence on these patients’ treatment(25). For instance, polymorphism where in cytochrome P450 enzymes could cause to metabolite to drug slowly or very fast. So patient give an overdose symptoms or no response to drug by changing the pharmacokinetics of drug metabolism, also it may cause an adverse drug reaction(26). Thereby , forecasting optimal dose of drug , inducing the harmful side effects can be provided by using polymorphism(27). In familial breast cancer, patients shows low survival rate to treatment with tamoxifen that is chemotherapeutic drug because of genetic variation in CYP2D6 that is seen as a poor metabolizer (28). There are some studies abour genetic testing on drug label including test for CYP450 polymorphisms.

Prognosis

Insteaf of using clinicopathologic parameters as a biomarker in biochemical testing for prognosis and selection of therapatic way for cancer patient , Genotyping or gene expression profiling by microarray and protein analysis by mass spectrometry is used for prognostic biomarkers with the understanding of the molecular mechanism of cancer subtypes(29).

Biomarkers can be used alone or with combination of other parameters for classify subgroups according to their risk rate and for leading to therapy decision. For example, tissue microarray analysis with combining molecular and clinical biomarker is more efficient than the clasical clinical parameter for patient who has renal cell carcinoma(30).

Approaches and Tools for Personalized Medicine

Instead of using PCR, fluorescence in situ hybridization, immunohistochemistry, and sequencing for personalized medicine testing, high throughput analyses that consist of microarray, mass spectrometry, second generation sequencing, array comparative genomic hybridization, and high-throughput single nucleotide polymorphism (SNP) analysis were started to use after human genome project . These techniques can analyse numerous target at the same time(31). New technologies improve sesitiveness, speciality, trueness of new b

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