There is evidence from a range of countries that clinical decisions regarding older men diagnosed with prostate cancer are based on the patient’s age, rather than their ability to benefit from treatment. However, geriatric oncology guidelines state that fit older men with prostate cancer should receive curative treatment.
The aims of this project were to: (a) document trends on prostate cancer treatment and survival at the population-level; (b) identify predictors of treatment receipt, with particular emphasis on age and co-morbidity; and (c) identify predictors of survival.
The project involved three phases. The first phase was a national postal survey of radiation oncologists and urologists to identify which clinical/medical and non-clinical factors impact on treatment decision-making. For each of 68 comorbid conditions (from ACE-27), clinicians were asked to rate the extent to which these would impact on a decision of whether or not to recommend radical prostatectomy, radiotherapy or androgen deprivation therapy. Clinicians were also invited to indicate which non-medical issues - including age, life expectancy, mobility, marital status, support at home, distance from hospital of treatment, likelihood of side effects following treatment, quality-of-life after treatment, patient’s and family’s preferences, and health insurance status – would impact on their treatment recommendations.
In the second phase, hospital in-patient episodes (HIPE records) were used to create various measures of co-morbidity for prostate cancer patients in Ireland. Time trends in, and predictors of, different treatment modalities were investigated. Specific attention was paid to determining the extent to which associations between age and curative and other forms of treatment could be explained by comorbidities.
The final phase of the project involved examining patterns of cause of death among prostate cancer patients in Ireland. Competing risk analysis was undertaken to estimate risk of prostate cancer specific mortality while accounting for other causes of death. This analysis investigated associations between clinical and socio-demographic factors and mortality. The effect of treatment was also investigated, using propensity score methods to account for systematic differences between those who receive treatment and those who do not.