Patient-Reported Outcomes After Radiation Therapy in Men With Prostate Cancer: A Systematic Review of Prognostic Tool Accuracy and Validity

Health-related quality of life in men with localized prostate cancer treated with radiotherapy: validation of an abbreviated version of the Expanded Prostate Cancer Index Composite for Clinical Practice in Spain

Background

Health-related quality of life (HRQoL) is greatly affected by prostate cancer (PCa) and associated treatments. This study aimed to measure the impact of radiotherapy on HRQoL and to further validate the Spanish version of the 16-item Expanded Prostate Cancer Index Composite (EPIC-16) in routine clinical practice.

Methods

An observational, non-interventional, multicenter study was conducted in Spain with localized PCa patients initiating treatment with external beam radiotherapy (EBRT) or brachytherapy (BQT). Changes from baseline in EPIC-16, University of California-Los Angeles Prostate Cancer Index (UCLA-PCI), and patient-perceived health status were longitudinally assessed at end of radiotherapy (V2) and 90 days thereafter (V3). Psychometric evaluations of the Spanish EPIC-16 were conducted.

Results

Of 516 patients enrolled, 495 were included in the analysis (EBRT, n = 361; BQT, n = 134). At baseline, mean (standard deviation [SD]) EPIC-16 global scores were 11.9 (7.5) and 10.3 (7.7) for EBRT and BQT patients, respectively; scores increased, i.e., HRQoL worsened, from baseline, by mean (SD) of 6.8 (7.6) at V2 and 2.4 (7.4) at V3 for EBRT and 4.2 (7.6) and 3.9 (8.2) for BQT patients. Changes in Spanish EPIC-16 domains correlated well with urinary, bowel, and sexual UCLA-PCI domains. EPIC-16 showed good internal consistency (Cronbach’s alpha = .84), reliability, and construct validity.

Conclusion

The Spanish EPIC-16 questionnaire demonstrated sensitivity, strong discriminative properties and reliability, and validity for use in clinical practice. EPIC-16 scores worsened after radiotherapy in different HRQoL domains; however, a strong tendency towards recovery was seen at the 3-month follow-up visit.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12955-021-01856-z.

Assessing concordance between patient-reported and investigator-reported CTCAE after proton beam therapy for prostate cancer

PURPOSE

We report acute patient-reported outcomes using CTCAE (PRO-CTCAE) of proton beam radiotherapy for high-risk or unfavorable intermediate-risk prostate cancer in a prospective clinical trial. PRO-CTCAE were correlated with investigator reported-CTCAE (IR-CTCAE) to assess the degree of concordance.

METHODS AND MATERIALS

11 PRO-CTCAE questions assessed gastrointestinal (GI), genitourinary (GU), or erectile function side effects. The correlation scheme between PRO-CTCAE and IR-CTCAE was independently developed by two physicians. Analyses of PRO-CTCAE and IR-CTCAE were conducted using both descriptive terms and the converted grade scores. The Kappa statistic described the degree of concordance.

RESULTS

55 patients were included. IR-CTCAE underestimated diarrhea compared to PRO-CTCAE at the end of treatment (EOT), with a 28% rate of underestimation (11% by ≥ 2 toxicity grades). Similarly, urinary tract pain was underestimated in 45% of cases (17% by ≥ 2 grades) at EOT. Differences were less pronounced at baseline or 3 months after radiotherapy. The incidence of urinary urgency and frequency tended to be overestimated prior to treatment (36% and 24%, respectively) but underestimated at EOT (35% and 31%, respectively). The degree of interference with daily activities was consistently overestimated by investigators (45%-85%). Finally, erectile dysfunction showed a 36-56% rate of discordance by ≥ 2 toxicity grades.

CONCLUSIONS

Our study shows a low agreement between IR-CTCAE and PRO-CTCAE in the setting of proton therapy for prostate cancer. Compared to patient-reported outcomes, physicians underestimated the frequency and severity of urinary symptoms and diarrhea at the end of treatment. Continued use of PROs should be strongly encouraged.

Electronic Patient-Reported Outcome Measures in Radiation Oncology: Initial Experience After Workflow Implementation

Background

Mobile health (mHealth) technologies are increasingly used in various medical fields. However, the potential of mHealth to improve patient care in radiotherapy by acquiring electronic patient reported outcome measures (ePROMs) during treatment has been poorly studied so far.

Objective

The aim of this study was to develop and implement a novel Web app (PROMetheus) for patients undergoing radiotherapy. Herein, we have reported our experience with a focus on feasibility, patient acceptance, and a correlation of ePROMs with the clinical course of the patients.

Methods

In the period between January and June 2018, 21 patients used PROMetheus to score side effects, symptoms, and quality of life–related parameters during and after their treatment. Items of the Patient Reported Outcome version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) were chosen based on the primary site of disease, 27 items for head and neck tumors, 21 items for thoracic tumors, and 24 items for pelvic tumors.

Results

In total, 17 out of the 21 patients (81%) regularly submitted ePROMs and more than 2500 data points were acquired. An average of 5.2, 3.5, and 3.3 min was required to complete the head and neck, thorax, and pelvis questionnaires, respectively. ePROMS were able to detect the occurrence of both expected and unexpected side effects during the treatment.

In addition, a gradual increase in the severity of side effects over the course the treatment and their remission afterward could be observed with ePROMs. In total, 9 out of the 17 patients (53%), mostly those with head and neck and thoracic cancers, reported PRO-CTCAE grade III or IV fatigue with severe impairments of activities of daily life.

Conclusions

This study shows the successful implementation of an ePROM system and a high patient acceptance. ePROMs have a great potential to improve patient care in radiotherapy by providing a comprehensive documentation of symptoms and side effects, especially of ones that are otherwise underreported.

A case-control study using motion-inclusive spatial dose-volume metrics to account for genito-urinary toxicity following high-precision radiotherapy for prostate cancer

Background and purpose

Material and methods

Results

Conclusions

Machine Learning and Radiogenomics: Lessons Learned and Future Directions

Due to the rapid increase in the availability of patient data, there is significant interest in precision medicine that could facilitate the development of a personalized treatment plan for each patient on an individual basis. Radiation oncology is particularly suited for predictive machine learning (ML) models due to the enormous amount of diagnostic data used as input and therapeutic data generated as output. An emerging field in precision radiation oncology that can take advantage of ML approaches is radiogenomics, which is the study of the impact of genomic variations on the sensitivity of normal and tumor tissue to radiation. Currently, patients undergoing radiotherapy are treated using uniform dose constraints specific to the tumor and surrounding normal tissues. This is suboptimal in many ways. First, the dose that can be delivered to the target volume may be insufficient for control but is constrained by the surrounding normal tissue, as dose escalation can lead to significant morbidity and rare. Second, two patients with nearly identical dose distributions can have substantially different acute and late toxicities, resulting in lengthy treatment breaks and suboptimal control, or chronic morbidities leading to poor quality of life. Despite significant advances in radiogenomics, the magnitude of the genetic contribution to radiation response far exceeds our current understanding of individual risk variants. In the field of genomics, ML methods are being used to extract harder-to-detect knowledge, but these methods have yet to fully penetrate radiogenomics. Hence, the goal of this publication is to provide an overview of ML as it applies to radiogenomics. We begin with a brief history of radiogenomics and its relationship to precision medicine. We then introduce ML and compare it to statistical hypothesis testing to reflect on shared lessons and to avoid common pitfalls. Current ML approaches to genome-wide association studies are examined. The application of ML specifically to radiogenomics is next presented. We end with important lessons for the proper integration of ML into radiogenomics.

Multi-atlas-based segmentation of prostatic urethra from planning CT imaging to quantify dose distribution in prostate cancer radiotherapy

BACKGROUND AND PURPOSE

Segmentation of intra-prostatic urethra for dose assessment from planning CT may help explaining urinary toxicity in prostate cancer radiotherapy. This work sought to: i) propose an automatic method for urethra segmentation in CT, ii) compare it with previously proposed surrogate models and iii) quantify the dose received by the urethra in patients treated with IMRT.

MATERIALS AND METHODS

A weighted multi-atlas-based urethra segmentation method was devised from a training data set of 55 CT scans of patients receiving brachytherapy with visible urinary catheters. Leave-one-out cross validation was performed to quantify the error between the urethra segmentation and the catheter ground truth with two scores: the centerlines distance (CLD) and the percentage of centerline within a certain distance from the catheter (PWR). The segmentation method was then applied to a second test data set of 95 prostate cancer patients having received 78Gy IMRT to quantify dose to the urethra.

RESULTS

Mean CLD was 3.25±1.2mm for the whole urethra and 3.7±1.7mm, 2.52±1.5mm, and 3.01±1.7mm for the top, middle, and bottom thirds, respectively. In average, 53% of the segmented centerlines were within a radius<3.5mm from the centerline ground truth and 83% in a radius<5mm. The proposed method outperformed existing surrogate models. In IMRT, urethra DVH was significantly higher than prostate DVH from V74Gy to V79Gy.

CONCLUSION

A multi-atlas-based segmentation method was proposed enabling assessment of the dose within the prostatic urethra.

Conventional Versus Hypofractionated Radiation Therapy for Localized or Locally Advanced Prostate Cancer: A Systematic Review and Meta-analysis along with Therapeutic Implications

PURPOSE

A systematic review and meta-analysis were conducted to evaluate the therapeutic outcomes of conventional radiation therapy (CRT) and hypofractionated radiation therapy (HRT) for localized or locally advanced prostate cancer (LLPCa).

METHODS AND MATERIALS

A total of 599 abstracts were extracted from 5 databases and screened in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Only phase III trials randomized between CRT and HRT in LLPCa with a minimum of 5 years of follow-up data were considered. The evaluated endpoints were biochemical failure, biochemical and/or clinical failure, overall mortality, prostate cancer-specific mortality, and both acute and late gastrointestinal (GI) and genitourinary (GU) (grade ≥2) toxicity.

RESULTS

Ten trials from 9 studies, with a total of 8146 patients (CRT, 3520; HRT, 4626; 1 study compared 2 HRT schedules with a common CRT regimen), were included in the evaluation. No significant differences were found in the patient characteristics between the 2 arms. However, the RT parameters differed significantly between CRT and HRT (P<.001 for all). The use of androgen deprivation therapy varied from 0% to 100% in both groups (mean ± standard deviation 43.3% ± 43.6% for CRT vs HRT; P=NS). The odds ratio, risk ratio, and risk difference (RD) between CRT and HRT for biochemical failure, biochemical and/or clinical failure, overall mortality, prostate cancer-specific mortality, acute GU toxicity, and late GU and GI toxicities were all nonsignificant. Nevertheless, the incidence of acute GI toxicity was 9.1% less with CRT (RD 0.091; odds ratio 1.687; risk ratio 1.470; P<.001 for all). On subgroup analysis, the patient groups with ≤66.8% versus >66.8% androgen deprivation therapy (RD 0.052 vs 0.136; P=.008) and <76% versus ≥76% full seminal vesicles in the clinical target volume (RD 0.034 vs 0.108; P<.001) were found to significantly influence the incidence of acute GI toxicity with HRT.

CONCLUSIONS

HRT provides similar therapeutic outcomes to CRT in LLPCa, except for a significantly greater risk of acute GI toxicity. HRT enables a reduction in the overall treatment time and offers patient convenience. However, the variables contributing to an increased risk of acute GI toxicity require careful consideration.

Tools for Predicting Clinical and Patient-reported Outcomes in Prostate Cancer Patients Undergoing Androgen Deprivation Therapy: A Systematic Review of Prognostic Accuracy and Validity

Androgen deprivation therapy (ADT) can result in a range of adverse symptoms that reduce patients' quality of life. Careful patient counseling on the likely clinical outcomes and adverse effects is therefore vital. The present systematic review was undertaken to identify and characterize all the tools used for the prediction of clinical and patient-reported outcome measures (PROMs) in patients with prostate cancer undergoing ADT. PubMed and EMBASE were systematically searched from 2007 to 2016. Search terms related to the inclusion criteria were: prostate cancer, clinical outcomes, PROMs, ADT, and prognosis. Titles and abstracts were reviewed to find relevant studies, which were advanced to full-text review. The reference lists were screened for additional studies. The Centre for Evidence Based Medicine critical appraisal of prognostic studies tool was applied. The search strategy identified 8755 studies. Of the 8755 studies, 22 on clinical outcomes were identified. However, no studies of PROMs were found. Nine tools could be used to predict clinical outcomes in treatment-naive patients and 10 in patients with recurrence. The Japan Cancer of the Prostate Risk Assessment (J-CAPRA) nomogram was the best performing and validated tool for the prediction of clinical outcomes in treatment-naive patients, and the Chi and Shamash prognostic indexes have been validated for use in patients with castration-resistant disease in different clinical contexts. Using the J-CAPRA nomogram should help clinicians deliver accurate, evidence-based counseling to patients undergoing primary ADT. A strong need exists for primary studies that derive and validate tools for the prediction of PROMs in patients undergoing ADT under any circumstance because these are currently absent from the literature.