Defining the role of surveillance in the management of localized prostate cancer

Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data

BACKGROUND

Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics.

OBJECTIVE

To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data.

DESIGN, SETTING, AND PARTICIPANTS

From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data.

RESULTS AND LIMITATIONS

The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent.

CONCLUSIONS

Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data.

PATIENT SUMMARY

Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.

Watching, waiting and uncertainty in prostate cancer

AIM

This study explores the problems and uncertainties of older men, with prostate cancer, who have undergone watchful waiting and the strategies they use to manage their concerns.

BACKGROUND

With life expectancy rising, the number of older men with prostate cancer has increased. Nearly 50% of all new prostate cancers are diagnosed in men over 70 years old. For many of these older men, improvements in medical care have increased the likelihood of living for years with prostate cancer. Thus, watchful waiting has been proposed as a reasonable alternative to treatment for older men with localized prostate cancer.

METHODS

A qualitative, descriptive design was used for this study. The results from interviews with 10 men who were undergoing watchful waiting for prostate cancer were analysed using the Mishel's Reconceptualized Uncertainty in Illness model.

RESULTS

Domains of uncertainty, appraisal of danger and appraisal of opportunity were identified and each was supported by participant's experience.

CONCLUSIONS

The results of the study may be used to expand the Uncertainty in Illness model and develop interventions for men undergoing watchful waiting for prostate cancer.

RELEVANCE TO CLINICAL PRACTICE

These findings may be used to enhance current nursing interventions for men electing for watchful waiting as an alternative to treatment for prostate cancer, including patient teaching and support services. Future study should examine the role of nurses in managing uncertainty, especially in patient teaching and in the development, implementation and evaluation of interventions to manage uncertainty.

Deferred treatment of localized prostate cancer in the elderly: the impact of the age and stage at the time of diagnosis on the treatment decision

OBJECTIVE

To assess the clinical behaviour of clinically localized prostate cancer in elderly patients monitored until progression, and the impact of clinical variables, i.e. clinical stage, Gleason score, the dynamics of prostate specific antigen (PSA) and age, on the natural history of the disease.

PATIENTS AND METHODS

Between February 1991 and January 1998, 54 patients (mean age 76.4 years, median 77 at the time of diagnosis) with clinically localized prostate cancer who elected for watchful waiting were identified. They were monitored regularly and treatment deferred until progression. Progression was defined as local stage progression (as assessed on a digital rectal examination), biochemical progression or metastasis. All patients who progressed were offered either radiation therapy or hormonal treatment. Each clinical variable was assessed by univariate and multivariate analysis to predict disease progression. The mean follow-up was 47 months.

RESULTS

Of the 54 patients, 28 (52%) progressed; 10 had biochemical, 11 local and four biochemical and local progression, and three developed metastasis. All the patients who progressed elected to receive hormonal treatment. The mean time to progression was 35 months. Gleason score (</= 6 and > 6), age (</= 75 and > 75 years) and serum PSA level (</= 10 and > 10 ng/mL) were statistically significant predictors of disease progression (P = 0.04, < 0.001 and 0.02, respectively). The clinical stage at the time of diagnosis had a borderline effect on disease progression (P = 0.06). On multivariate analysis, Gleason score and PSA level were statistically significant predictors of disease progression.

CONCLUSION

These results suggest that the treatment of prostate cancer should not be deferred in patients aged > 75 years with a good performance status when the biopsy has a Gleason score >/= 6 and the serum PSA level is >/= 10 ng/mL.

Decision analysis for treatment of early stage prostate cancer

We performed a decision analysis to evaluate the usefulness of pretreatment prediction of clinically significant or insignificant tumor in patients with prostate-specific antigen (PSA)-detected stage T1c prostate cancer nonpalpable on rectal examination. Analysis was done for otherwise healthy subjects with 20 years of life expectancy. The prevalence of insignificant tumor among those with T1c prostate cancer was initially assumed to be 0.2. Quality-adjusted life expectancy was calculated and compared between 2 strategies; one with prediction-based selection of either radical prostatectomy or watchful waiting and the other with unselective assignment of one of the treatments. The selection strategy was superior when the sensitivity and specificity for detecting clinically significant tumor were 0.92 and 0.73, respectively, as reported by Epstein et al. (1994) using criteria of PSA density and Gleason score in a needle biopsy specimen. Sensitivity analysis revealed that the prediction-based selection strategy is preferred, with sensitivity and specificity constant, when the prevalence of insignificant tumor exceeds 0.16. On the other hand, when the prevalence of insignificant tumor is kept constant at 0.2, sensitivity should be 0.85 or higher for the prediction strategy to be preferred. As the prevalence of insignificant tumor among those with T1c prostate cancer increased, the prediction-based selection strategy is preferred with lower values of sensitivity and specificity for detecting significant tumor. These results suggest that a selective treatment strategy of either radical or conservative treatment based on pretreatment prediction for significant tumor is a beneficial alternative to radical prostatectomy unselectively assigned to all patients at the T1c stage, if a reasonable accuracy in prediction is attained.