Real-world Evidence to Estimate Prostate Cancer Costs for First-line Treatment or Active Surveillance

Magnani, Christopher J.; Bievre, Nicolas; Baker, Laurence C.; Brooks, James D.; Blayney, Douglas W.; Hernandez‐Boussard, Tina

doi:10.1016/j.euros.2020.11.004

Cited by 17 publications

(22 citation statements)

References 30 publications

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“…EHRs were developed for billing purposes and are designed to act as central repositories of structured data such as laboratory values and house unstructured data such as physician notes. EHRs also provide opportunities for secondary uses including identification of patients for clinical trial enrollment, conducting pragmatic clinical trials, carrying out post-market surveillance, monitoring and improving adherence to clinical guidelines, cost analyses and population-based studies ( 19 , 22 , 25 , 26 ). Furthermore, emerging evidence suggests that clinical care could be improved through EHR-based automated decision-making aides and risk calculators to facilitate personalized care at the bedside ( 27 ).…”

Section: Discussionmentioning

confidence: 99%

Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage

Bozkurt

Magnani²,

Seneviratne³

et al. 2022

Front. Digit. Health

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BackgroundExplicit documentation of stage is an endorsed quality metric by the National Quality Forum. Clinical and pathological cancer staging is inconsistently recorded within clinical narratives but can be derived from text in the Electronic Health Record (EHR). To address this need, we developed a Natural Language Processing (NLP) solution for extraction of clinical and pathological TNM stages from the clinical notes in prostate cancer patients.MethodsData for patients diagnosed with prostate cancer between 2010 and 2018 were collected from a tertiary care academic healthcare system's EHR records in the United States. This system is linked to the California Cancer Registry, and contains data on diagnosis, histology, cancer stage, treatment and outcomes. A randomly selected sample of patients were manually annotated for stage to establish the ground truth for training and validating the NLP methods. For each patient, a vector representation of clinical text (written in English) was used to train a machine learning model alongside a rule-based model and compared with the ground truth.ResultsA total of 5,461 prostate cancer patients were identified in the clinical data warehouse and over 30% were missing stage information. Thirty-three to thirty-six percent of patients were missing a clinical stage and the models accurately imputed the stage in 21–32% of cases. Twenty-one percent had a missing pathological stage and using NLP 71% of missing T stages and 56% of missing N stages were imputed. For both clinical and pathological T and N stages, the rule-based NLP approach out-performed the ML approach with a minimum F1 score of 0.71 and 0.40, respectively. For clinical M stage the ML approach out-performed the rule-based model with a minimum F1 score of 0.79 and 0.88, respectively.ConclusionsWe developed an NLP pipeline to successfully extract clinical and pathological staging information from clinical narratives. Our results can serve as a proof of concept for using NLP to augment clinical and pathological stage reporting in cancer registries and EHRs to enhance the secondary use of these data.

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Section: Discussionmentioning

confidence: 99%

Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage

Bozkurt

Magnani²,

Seneviratne³

et al. 2022

Front. Digit. Health

Self Cite

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“…However, clinical data used in the mathematical models are hypothetical 8,10 and may deviate from data of actual clinical settings. Moreover, because EHR are used in the healthcare systems of specific regions, the generalizability of studies using EHR 11,15,16 is hindered by differing clinical practices, local populations, and demographics of individuals in the insurance systems. In this study, we performed a cost analysis using data from the J-CAP 14 study (a nationwide observational study reflecting recent trends in Japan) and the PRIAS-JAPAN study (a prospective observational study of the Japanese AS cohort).…”

Section: Discussionmentioning

confidence: 99%

“…Promotion of AS is an important strategy to reduce the treatment costs for low‐risk PCa. To date, several studies have compared AS with other treatments using a mathematical model 5–10 or electronic health records (EHR) such as Medicare 11–13 . However, no study has analyzed the outcomes using actual treatment trends in Japan.…”

Section: Introductionmentioning

confidence: 99%

“…To date, several studies have compared AS with other treatments using a mathematical model [5][6][7][8][9][10] or electronic health records (EHR) such as Medicare. [11][12][13] However, no study has analyzed the outcomes using actual treatment trends in Japan. Thus, this study aimed to evaluate the costeffectiveness of AS compared with that of robot-assisted laparoscopic prostatectomy (RALP), intensity-modulated radiation therapy (IMRT), brachytherapy (BT), and HT for men diagnosed with low-risk localized PCa in Japan.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of the medical costs between active surveillance and other treatments for early prostate cancer in Japan using data from the PRIAS‐JAPAN study

et al. 2022

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Abbreviations & Acronyms AS = active surveillance BT = brachytherapy DPC = diagnosis procedure combination EBRT = external beam radiation therapy EHR = electronic health records GS = Gleason score HT = hormone therapy IMRT = intensity-modulated radiation therapy JPY = Japanese yen LH-RH = luteinizing hormonereleasing hormone MRI = magnetic resonance imaging PCa = prostate cancer PSA = prostate-specific antigen QALYs = quality adjusted life years QOL = quality of life RALP = robot-assisted laparoscopic prostatectomy USD = United States dollar

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“…As our focus was on AS regimens and not definitive treatments, we limited our analysis to default first-line treatment after progression on AS with surgery for men under 70 years old and intensity-modulated radiation therapy (IMRT) for older men, a decision guided by previous studies that assessed definitive treatment options. 11,17,20 Up-front management with either definitive treatment was also assessed for comparison.…”

Section: Modelingmentioning

confidence: 99%

Cost-Effectiveness Analysis and Microsimulation of Serial Multiparametric Magnetic Resonance Imaging in Active Surveillance of Localized Prostate Cancer

et al. 2022

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Purpose:Many localized prostate cancers will follow an indolent course. Management has shifted toward active surveillance (AS), yet an optimal regimen remains controversial especially regarding expensive multiparametric magnetic resonance imaging (MRI). We aimed to assess cost-effectiveness of MRI in AS protocols.Materials and Methods:A probabilistic microsimulation modeled individual patient trajectories for men diagnosed with low-risk cancer. We assessed no surveillance, up-front treatment (surgery or radiation), and scheduled AS protocols incorporating transrectal ultrasound-guided (TRUS) biopsy or MRI based regimens at serial intervals. Lifetime quality-adjusted life-years and costs adjusted to 2020 US$ were used to calculate expected net monetary benefit at $50,000/quality-adjusted life-year and incremental cost-effectiveness ratios. Uncertainty was assessed with probabilistic sensitivity analysis and linear regression metamodeling.Results:Conservative management with AS outperformed up-front definitive treatment in a modeled cohort reflecting characteristics from a multi-institutional trial. Biopsy decision conditional on positive imaging (MRI triage) at 2-year intervals provided the highest expected net monetary benefit (incremental cost-effectiveness ratio $44,576). Biopsy after both positive and negative imaging (MRI pathway) and TRUS biopsy based regimens were not cost-effective. MRI triage resulted in fewer biopsies while reducing metastatic disease or cancer death. Results were sensitive to test performance and cost. MRI triage was the most likely cost-effective strategy on probabilistic sensitivity analysis.Conclusions:For men with low-risk prostate cancer, our modeling demonstrated that AS with sequential MRI triage is more cost-effective than biopsy regardless of imaging, TRUS biopsy alone or immediate treatment. AS guidelines should specify the role of imaging, and prospective studies should be encouraged.

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Real-world Evidence to Estimate Prostate Cancer Costs for First-line Treatment or Active Surveillance

Cited by 17 publications

References 30 publications

Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage

Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage

Comparison of the medical costs between active surveillance and other treatments for early prostate cancer in Japan using data from the PRIAS‐JAPAN study

Cost-Effectiveness Analysis and Microsimulation of Serial Multiparametric Magnetic Resonance Imaging in Active Surveillance of Localized Prostate Cancer

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