Influence of Sociodemographic Factors on Definitive Intervention Among Low-risk Active Surveillance Patients

Influential Factors Impacting Treatment Decision-making and Decision Regret in Patients with Localized or Locally Advanced Prostate Cancer: A Systematic Literature Review

CONTEXT

Treatment decision-making (TDM) for patients with localized (LPC) or locally advanced (LAPC) prostate cancer is complex, and post-treatment decision regret (DR) is common. The factors driving TDM or predicting DR remain understudied.

OBJECTIVE

Two systematic literature reviews were conducted to explore the factors associated with TDM and DR.

EVIDENCE ACQUISITION

Three online databases, select congress proceedings, and gray literature were searched (September 2022). Publications on TDM and DR in LPC/LAPC were prioritized based on the following: 2012 onward, ≥100 patients, journal article, and quantitative data. The Preferred Reporting Items Reviews and Meta-analyses guidelines were followed. Influential factors were those with p < 0.05; for TDM, factors described as "a decision driver", "associated", "influential", or "significant" were also included. The key factors were determined by number of studies, consistency of evidence, and study quality.

EVIDENCE SYNTHESIS

Seventy-five publications (68 studies) reported TDM. Patient participation in TDM was reported in 34 publications; overall, patients preferred an active/shared role. Of 39 influential TDM factors, age, ethnicity, external factors (physician recommendation most common), and treatment characteristics/toxicity were key. Forty-nine publications reported DR. The proportion of patients experiencing DR varied by treatment type: 7-43% (active surveillance), 12-57% (radical prostatectomy), 1-49% (radiotherapy), 28-49% (androgen-deprivation therapy), and 21-47% (combination therapy). Of 42 significant DR factors, treatment toxicity (sexual/urinary/bowel dysfunction), patient role in TDM, and treatment type were key.

CONCLUSIONS

The key factors impacting TDM were physician recommendation, age, ethnicity, and treatment characteristics. Treatment toxicity and TDM approach were the key factors influencing DR. To help patients navigate factors influencing TDM and to limit DR, a shared, consensual TDM approach between patients, caregivers, and physicians is needed.

PATIENT SUMMARY

We looked at factors influencing treatment decision-making (TDM) and decision regret (DR) in patients with localized or locally advanced prostate cancer. The key factors influencing TDM were doctor's recommendation, patient age/ethnicity, and treatment side effects. A shared, consensual TDM approach between patients and doctors was found to limit DR.

Patterns of multispecialty care for low- and intermediate-risk prostate cancer in the use of active surveillance

BACKGROUND

Multidisciplinary models of care have been advocated for prostate cancer (PC) to promote shared decision-making and facilitate quality care. Yet, how this model applies to low-risk disease where the preferred management is expectant remains unclear. Accordingly, we examined recent practice patterns in specialty visits for low/intermediate-risk PC and resultant use of active surveillance (AS).

METHODS

Using SEER-Medicare, we ascertained whether patients saw urology and radiation oncology (i.e., multispecialty care) versus urology alone, based on self-designated specialty codes, for newly diagnosed PC from 2010 to 2017. We also examined the association with AS, defined as the absence of treatment within 12 months of diagnosis. Time trends were analyzed using Cochran-Armitage test. Chi-squared and logistic regression analyses were applied to compare sociodemographic and clinicopathologic characteristics between these models of care.

RESULTS

The proportion of patients seeing both specialists was 35.5% and 46.5% for low- and intermediate-risk patients respectively. Trend analysis showed a decline in multispecialty care in low-risk patients (44.1% to 25.3% years 2010-2017; P < 0.001). Between 2010 and 2017, the use of AS increased 40.9% to 68.6% (P < 0.001) and 13.1% to 24.6% (P < 0.001) for patients seeing urology and those seeing both specialists respectively. Age, urban residence, higher education, SEER region, co-morbidities, frailty, Gleason score, predicted receipt of multispecialty care (all P < 0.02).

CONCLUSIONS

Uptake of AS among men with low-risk PC has occurred primarily under the purview of urologists. While selection is certainly at play, these data suggest that multispecialty care may not be required to promote the utilization of AS for men with low-risk PC.

Prostate cancer mortality rates in low- and favorable intermediate-risk active surveillance patients: a population-based competing risks analysis

PURPOSE

To determine prostate cancer (PCa) and other-cause mortality rates in low- and favorable intermediate-risk (FIR) active surveillance (AS) patients.

METHODS

The SEER Prostate with Watchful Waiting database was used to identify men diagnosed with NCCN low or FIR PCa, between 2010 and 2015, managed with AS. FIR patients were subdivided into three subgroups, based on their intermediate risk factor: grade group two (GG2), PSA 10-20 ng/ml or cT2b-c disease. Cumulative incidence function curves with other-cause mortality as the competing risk were utilized. Predictors of PCa mortality were assessed using multivariable regression analysis with semi-parametric proportional hazards modeling.

RESULTS

Among 70,871 patients, 48,127 (67.9%) had low and 22,744 (32.1%) had FIR disease. Median patient age was 64.0 years, and median PSA was 5.70 ng/ml. Median follow-up was 49.0 months. There were 166 (0.2%) PCa and 3,176 (4.48%) other-cause mortalities. The 5-year mortality rates in the low and FIR cohorts overall were 0.29% and 0.28%, respectively (p = 0.64). Within the FIR cohort, the corresponding rates were highest in the PSA 10-20 ng/ml subgroup at 0.73%, followed by 0.32% for GG2 FIR and 0.052% for cT2b-c FIR disease (p < 0.001). Older age at diagnosis (sHR 2.38, p = 0.006), Medicaid insurance (sHR: 2.58, p < 0.001), low socioeconomic (sHR 1.39, p = 0.032), and non-married statuses (sHR: 2.58, p < 0.001) were associated with increased PCa mortality.

CONCLUSION

Intermediate-term PCa mortality rates in FIR PCa patients are non-significantly different to those with low-risk PCa. However, there is significant within-group heterogeneity, with PCa mortality rates significantly higher in the PSA 10-20 subgroup.

Understanding Hospital-Level Patterns of Nonoperative Management for Low-risk Thyroid and Kidney Cancer

IMPORTANCE

There is a growing trend toward conservative management for certain low-risk cancers. Hospital and health-system factors may play a role in determining how these patients are managed.

OBJECTIVE

To explore the contribution of hospitals on patients' odds of nonoperative management for low-risk cancer.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, individuals with low-risk papillary thyroid cancer and solitary kidney masses were identified, and those receiving nonoperative management vs surgery were compared. Patients with low-risk thyroid cancer and kidney cancer from 2015 to 2017 eligible for nonoperative management according to National Comprehensive Cancer Network guidelines within the National Cancer Database were included. Data were analyzed from October 2021 to March 2022.

MAIN OUTCOMES AND MEASURES

For each facility, the proportion of these patients who received operative and nonoperative management was calculated. A mixed-effects logistic regression model with a hospital-level random effects term was used to calculate factors associated with nonoperative management. Between-hospital variability was assessed using ranked caterpillar plots.

RESULTS

There were 19 570 individuals with low-risk thyroid cancer (15 344 women [78.4%]; mean [SD] age, 51.74 [95% CI, 51.39-52.08] years) and 41 403 with kidney cancer (25 253 men [61.0%]; mean [SD] age, 61.93 [95% CI, 61.70-62.17] years). In the group with low-risk thyroid cancer, 2.1% (419 patients) received nonoperative management, and in the group with kidney cancer, 9.5% (3928 patients) received nonoperative management. This varied between hospitals from 1.1% (95% CI, 1.0%-1.1%) in the bottom decile to 10.3% (95% CI, 8.0%-12.4%) in the top decile for low-risk thyroid cancer, and from 4.3% (95% CI, 4.1%-4.4%) in the bottom decile to 24.6% (95% CI, 22.7%-26.5%) in the top decile for small kidney masses. For both cancers, age was associated with increased odds of nonoperative treatment. The hospital-level odds of nonoperative management of thyroid and kidney cancer using unadjusted probabilities (observed proportions) were minimally correlated (Spearman ρ = .33; P < .001).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that although health systems factors may be associated with the tendency to pursue nonoperative management, hospital-level factors may differ when comparing unrelated cancers.

Intensity of observation with active surveillance or watchful waiting in men with prostate cancer in the United States

BACKGROUND

Population-based studies assessing various active surveillance (AS) protocols for prostate cancer, to date, have inferred AS participation by the lack of definitive treatment and use of post-diagnostic testing. This is problematic as evidence suggests that most men do not adhere to AS protocols. We sought to develop a novel method of identifying men on AS or watchful waiting (WW) independent of post-diagnostic testing and aimed to identify possible predictors of follow-up intensity in men on AS/WW.

METHODS

A predictive model was developed using SEER watchful waiting data to identify men ≥66 years on AS between 2010-2015, irrespective of post-diagnostic testing, and applied to SEER-Medicare database. AS intensity among different variables including age, prostate-specific antigen (PSA) level, number of total and positive biopsy cores, Charlson comorbidity index, race (Black vs. non-Black), US census region, and county poverty, income, and education levels were compared using multivariable regression analyses for PSA testing, surveillance biopsy, and magnetic resonance imaging (MRI).

RESULTS

A total of 2238 men were identified as being on AS. Of which, 81%, 33%, and 10% had a PSA test, surveillance biopsy, and MRI scan within 1-2 years, respectively. On multivariable analyses, Black men were less likely to have a PSA test (adjusted rate ratio [ARR] 0.60, 95% CI: 0.53-0.69), MRI scan (ARR 0.40, 95% CI: 0.24-0.68), and surveillance biopsy (ARR 0.71, 95% CI: 0.55-0.92) than non-Black men. Men within the highest income quintile were more likely to undergo PSA test (ARR 1.16, 95% CI: 1.05-1.27) and MRI scan (ARR 1.60, 95% CI 1.15-2.27) compared to men with the lowest income.

CONCLUSIONS

Black men and men with lower incomes on AS underwent less rigorous monitoring. Further study is needed to understand and ameliorate differences in AS rigor stemming from sociodemographic differences.

Lifestyle and sociodemographic factors associated with treatment choice of clinically localized prostate cancer in an equal access healthcare system

Sociodemographic and lifestyle factors may play a role in determining whether patients with clinically localized prostate cancer (PC) are managed with active surveillance (AS), radical prostatectomy (RP), or radiation therapy (RT); however, these relationships have not been well examined. In a cross-sectional study conducted within an equal access healthcare system, multivariable adjusted regression analysis revealed that living with a spouse or partner was associated with a 65% lower chance of being managed by RT (P = 0.001) and 57% lower risk of being managed by AS (P = 0.042) compared with RP. No other sociodemographic or lifestyle factors were independently associated with treatment modality.