scholarly journals Structured Reporting of Rectal Cancer Staging and Restaging: A Consensus Proposal

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2135
Author(s):  
Vincenza Granata ◽  
Damiano Caruso ◽  
Roberto Grassi ◽  
Salvatore Cappabianca ◽  
Alfonso Reginelli ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Correlation Coefficient ◽  
Clinical Decision Making ◽  
Intraclass Correlation ◽  
Clinical Decision ◽  
Cancer Staging ◽  
Structured Reporting ◽  
Quality Analysis ◽  
Promising Tool ◽  
Structured Reports

Background: Structured reporting (SR) in oncologic imaging is becoming necessary and has recently been recognized by major scientific societies. The aim of this study was to build MRI-based structured reports for rectal cancer (RC) staging and restaging in order to provide clinicians all critical tumor information. Materials and Methods: A panel of radiologist experts in abdominal imaging, called the members of the Italian Society of Medical and Interventional Radiology, was established. The modified Delphi process was used to build the SR and to assess the level of agreement in all sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess the internal consistency of each section and to measure the quality analysis according to the average inter-item correlation. The intraclass correlation coefficient (ICC) was also evaluated. Results: After the second Delphi round of the SR RC staging, the panelists’ single scores and sum of scores were 3.8 (range 2–4) and 169, and the SR RC restaging panelists’ single scores and sum of scores were 3.7 (range 2–4) and 148, respectively. The Cα correlation coefficient was 0.79 for SR staging and 0.81 for SR restaging. The ICCs for the SR RC staging and restaging were 0.78 (p < 0.01) and 0.82 (p < 0.01), respectively. The final SR version was built and included 53 items for RC staging and 50 items for RC restaging. Conclusions: The final version of the structured reports of MRI-based RC staging and restaging should be a helpful and promising tool for clinicians in managing cancer patients properly. Structured reports collect all Patient Clinical Data, Clinical Evaluations and relevant key findings of Rectal Cancer, both in staging and restaging, and can facilitate clinical decision-making.

scholarly journals Preoperative staging of rectal cancer: Role of 3D endorectal ultrasonography

2012 ◽  
Vol 59 (2) ◽  
pp. 57-61 ◽  
Author(s):  
Giulio Santoro
Keyword(s):  
Rectal Cancer ◽  
Clinical Decision Making ◽  
Preoperative Staging ◽  
Three Dimensional ◽  
Good Deal ◽  
Clinical Decision ◽  
Cancer Staging ◽  
Relevant Information ◽  
Endorectal Ultrasonography ◽  
Cross Sectional

Endorectal ultrasonography has become important part of preoperative staging of rectal cancer, providing adequate information for clinical decision- making in many cases. However, with the currently available ultrasonographic equipment and techniques, a good deal of relevant information may remain hidden. The advent of high-resolution three-dimensional endoluminal ultrasound, constructed from a synthesis of standard two-dimensional cross-sectional images, and of "Volume Render Mode," a technique to analyze information inside a threedimensional volume, promises to improve the accuracy of rectal cancer staging. The anatomic structures in the pelvis, the axial and longitudinal extension of the tumor, the presence of slight or massive submucosal invasion in early rectal cancer may be imaged in greater detail. This additional information will bring an improvement for both planning and conduct of surgical procedures.

Computer-Assisted Reporting and Decision Support in Standardized Radiology Reporting for Cancer Imaging

2021 ◽  
pp. 426-434
Author(s):  
Bernardo C. Bizzo ◽  
Renata R. Almeida ◽  
Tarik K. Alkasab
Keyword(s):  
Decision Support ◽  
Improve Patient Safety ◽  
Cancer Imaging ◽  
Clinical Decision ◽  
Structured Reporting ◽  
Computer Assisted ◽  
Radiology Reporting ◽  
Multiple Sources ◽  
Structured Reports ◽  
Value Based Care

PURPOSE Recent advances in structured reporting are providing an opportunity to enhance cancer imaging assessment to drive value-based care and improve patient safety. METHODS The computer-assisted reporting and decision support (CAR/DS) framework has been developed to enable systematic ingestion of guidelines as clinical decision structured reporting tools embedded within the radiologist's workflow. RESULTS CAR/DS tools can reduce the radiology reporting variability and increase compliance with clinical guidelines. The lung cancer use-case is used to describe various scenarios of a cancer imaging structured reporting pathway, including incidental findings, screening, staging, and restaging or continued care. Various aspects of these tools are also described using cancer-related examples for different imaging modalities and applications such as calculators. Such systems can leverage artificial intelligence (AI) algorithms to assist with the generation of structured reports and there are opportunities for new AI applications to be created using the structured data associated with CAR/DS tools. CONCLUSION These AI-enabled systems are starting to allow information from multiple sources to be integrated and inserted into structured reports to drive improvements in clinical decision support and patient care.

scholarly journals The Role of Micro-RNAs and Circulating Tumor Markers as Predictors of Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

2020 ◽  
Vol 21 (19) ◽  
pp. 7040 ◽  
Author(s):  
Fatima Domenica Elisa De Palma ◽  
Gaetano Luglio ◽  
Francesca Paola Tropeano ◽  
Gianluca Pagano ◽  
Maria D’Armiento ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Clinical Decision Making ◽  
Locally Advanced ◽  
Therapy Response ◽  
Predictive Biomarkers ◽  
Advanced Rectal Cancer ◽  
Clinical Decision ◽  
Locally Advanced Rectal Cancer ◽  
Specific Expression ◽  
Micro Rnas

The response to neoadjuvant chemoradiation (nCRT) is a critical step in the management of locally advanced rectal cancer (LARC) patients. Only a minority of LARC patients responds completely to neoadjuvant treatments, thus avoiding invasive radical surgical resection. Moreover, toxic side effects can adversely affect patients’ survival. The difficulty in separating in advances responder from non-responder patients affected by LARC highlights the need for valid biomarkers that guide clinical decision-making. In this context, microRNAs (miRNAs) seem to be promising candidates for predicting LARC prognosis and/or therapy response, particularly due to their stability, facile detection, and disease-specific expression in human tissues, blood, serum, or urine. Although a considerable number of studies involving potential miRNA predictors to nCRT have been conducted over the years, to date, the identification of the perfect miRNA signatures or single miRNA, as well as their use in the clinical practice, is still representing a challenge for the management of LARC patients. In this review, we will first introduce LARC and its difficult management. Then, we will trace the scientific history and the key obstacles for the identification of specific miRNAs that predict responsiveness to nCRT. There is a high potential to identify non-invasive biomarkers that circulate in the human bloodstream and that might indicate the LARC patients who benefit from the watch-and-wait approach. For this, we will critically evaluate recent advances dealing with cell-free nucleic acids including miRNAs and circulating tumor cells as prognostic or predictive biomarkers.

Reirradiation and/or surgery for locoregionally recurrent rectal cancer: A systemic review and meta-analyses.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15159-e15159
Author(s):  
Chai Hong Rim ◽  
Jeongshim Lee
Keyword(s):  
Rectal Cancer ◽  
Clinical Decision Making ◽  
Late Complication ◽  
Clinical Decision ◽  
Late Complications ◽  
Local Control Rate ◽  
Systemic Review ◽  
Cochrane Library ◽  
The Difference ◽  
Grade 3

e15159 Background: Locoregional recurrence of rectal cancer (LRRC) might be occurred even after combination treatments including surgery and pelvic radiotherapy. Re-irradiation might provide the control of recurrence and/or symptomatic palliation, but possible complications are fearful hindrances. This study is to integrate information from various clinical studies, regarding re-irradiation and/or surgery of LRRC, and to provide practical information for clinical decision making. Methods: We searched four databases including pubmed, MEDLINE, Cochrane library, and Embase. The primary endpoint was overall survival (OS), and secondary endpoints were complications of grade ≥3, local control rate (LC), and symptomatic palliation rate. Results: A total of 17 studies, involving 18 cohorts and 744 patients with LRRC were included. Median OS among included studies ranged from 10 to 45 months (median: 24.5 months). Pooled 1-, 2-, and 3- year OS rates for all LRRC patients were 76.1% [95% confidence interval (CI): 61.7-86.3], 49.1% (38.5-59.7), and 38.3% (30.2-47.2), respectively. For patients who underwent re-irradiation and surgery (OP group), pooled 1-, 2-, and 3- year OS rates were 85.9% (95% CI: 74.0-92.9), 71.8% (54.6-84.4), and 51.7% (39.4-63.8). For patients who underwent re-irradiation but not surgery (non-OP group), pooled 1-, 2-, and 3-year OS rates were 63.5% (95% CI: 51.1-74.4), 34.2% (20.4-51.2), and 23.8% (15.4-34.8). The difference between two subgroups were significant for all 3 years analyses. Pooled 1-, 2-, and 3- year LC rates for OP group were 84.4% (95% CI: 75.5-90.4), 63.8% (55.2-71.5), and 46.9% (39.6-54.4), and for non-OP group were 72.0% (95% CI: 48.8-87.4), 54.8% (28.6-78.5), and 44.6% (16.6-76.5). The difference between subgroups were not statistically significant for all 3 years analyses. Pooled overall grade ≥3 acute complication rate was 11.7% (95% CI: 6.7-19.5), and for late complication was 25.5% (95% CI: 16.7-40.0). Patients who underwent surgery had a higher risk of grade ≥3 late complications (OR: 6.39, 95% CI: 3.2-12.7). Pooled symptomatic palliation rate was 75.2% (95% CI: 67.3-81.8). Conclusions: Re-irradiation and/or surgery might be an option with oncologic and palliative efficacies, where combined surgery provided more favorable survival outcome. However, late complication should be carefully considered especially when combined with surgery.

scholarly journals Modeling agreement on bounded scales

2017 ◽  
Vol 27 (11) ◽  
pp. 3460-3477 ◽  
Author(s):  
Sophie Vanbelle ◽  
Emmanuel Lesaffre
Keyword(s):  
Normal Distribution ◽  
Correlation Coefficient ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Concordance Correlation Coefficient ◽  
Concordance Correlation ◽  
Behavioral Sciences ◽  
Score Distribution ◽  
Outcome Scores ◽  
The Impact

Agreement is an important concept in medical and behavioral sciences, in particular in clinical decision making where disagreements possibly imply a different patient management. The concordance correlation coefficient is an appropriate measure to quantify agreement between two scorers on a quantitative scale. However, this measure is based on the first two moments, which could poorly summarize the shape of the score distribution on bounded scales. Bounded outcome scores are common in medical and behavioral sciences. Typical examples are scores obtained on visual analog scales and scores derived as the number of positive items on a questionnaire. These kinds of scores often show a non-standard distribution, like a J- or U-shape, questioning the usefulness of the concordance correlation coefficient as agreement measure. The logit-normal distribution has shown to be successful in modeling bounded outcome scores of two types: (1) when the bounded score is a coarsened version of a latent score with a logit-normal distribution on the [0,1] interval and (2) when the bounded score is a proportion with the true probability having a logit-normal distribution. In the present work, a model-based approach, based on a bivariate generalization of the logit-normal distribution, is developed in a Bayesian framework to assess the agreement on bounded scales. This method permits to directly study the impact of predictors on the concordance correlation coefficient and can be simply implemented in standard Bayesian softwares, like JAGS and WinBUGS. The performances of the new method are compared to the classical approach using simulations. Finally, the methodology is used in two different medical domains: cardiology and rheumatology.

scholarly journals A Hospital-Wide Intervention to Improve Compliance With TNM Cancer Staging Documentation

2021 ◽  
pp. 1-10
Author(s):  
Jason H. Lee ◽  
Tariq Mohamed ◽  
Celia Ramsey ◽  
Jihoon Kim ◽  
Shelly Kane ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Quality Improvement ◽  
Clinical Decision Making ◽  
Compliance Rate ◽  
Clinical Decision ◽  
Cancer Staging ◽  
Marrow Transplant ◽  
Improvement Project ◽  
Logistic Regression Models ◽  
Oncologic Patients

Background: Accurate oncologic staging meeting clinical practice guidelines is essential for guideline adherence, quality assessment, and survival outcomes. However, timely and uniform documentation in the electronic health record (EHR) at the time of diagnosis is a challenge for providers. This quality improvement project aimed to increase provider compliance of timely clinical TNM (cTNM) or pathologic TNM (pTNM) staging for newly diagnosed oncologic patients. Methods: Providers in the following site-specific oncologic teams were included: head and neck, skin, breast, genitourinary, gastrointestinal, lung and thoracic, gynecologic, colorectal, and bone marrow transplant. Interventions to facilitate timely cTNM and pTNM staging included standardized EHR-based workflows, learning modules, stakeholder meetings, and individualized provider training sessions. For most teams, staging was considered compliant if it was completed in the EHR within the first 7 days of the calendar month after the date of the patient visit. Factors associated with staging compliance were analyzed using logistic regression models. Results: From January 1, 2014, to December 31, 2018, 7,787 preintervention and 5,152 postintervention new patient visits occurred. During the preintervention period, staging was compliant in 5.6% of patients compared with 67.4% of patients after intervention (P<.001). In the final month of the postintervention period, the overall staging compliance rate was 78.1%. At most recent tracking, staging compliance was 95%, 97%, and 93% in December 2019, January 2020, and February 2020, respectively. Logistic regression found that increasing years of provider experience was associated with decreased staging compliance. Conclusions: High rates of staging compliance in complex multidisciplinary academic oncologic practice models can be achieved via comprehensive quality improvement and structured initiatives. This approach serves as a model for improving oncologic documentation systems to facilitate clinical decision-making and multidisciplinary coordination of care.

Management Driven Structured Reporting in Ovarian Cancer

2019 ◽  
Vol 03 (02) ◽  
pp. 153-162
Author(s):  
Anuradha Chandramohan ◽  
Sourav Panda ◽  
Anitha Thomas ◽  
Rachel Chandy ◽  
Anjana Joel ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Structured Reporting ◽  
Imaging Features ◽  
Advanced Stage ◽  
Anatomical Structures ◽  
Radiology Reports ◽  
Team Setting

AbstractSince majority (80%) of ovarian cancer patients present at an advanced stage, imaging performed on these patients have numerous findings. The combination of multiple findings on imaging, complexity of anatomical structures which are involved in ovarian cancer, and the need to perceive certain subtle imaging features which would impact management often makes it challenging to systematically review images of these patients. Similarly, it is difficult to effectively communicate these findings in radiology reports. Structured reporting that is geared toward clinical decision-making has been an area of recognized need. An understanding of the review areas, which aid clinical decision-making in a multidisciplinary team setting at our institution led us to the proposed structured reporting template for ovarian cancer. Through this review, the authors would like to share this reporting template with examples.

scholarly journals Structured Reporting of Lung Cancer Staging: A Consensus Proposal

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1569
Author(s):  
Vincenza Granata ◽  
Roberto Grassi ◽  
Vittorio Miele ◽  
Anna Rita Larici ◽  
Nicola Sverzellati ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Correlation Coefficient ◽  
Clinical Data ◽  
Mean Value ◽  
Structured Reporting ◽  
Quality Analysis ◽  
Cronbach’S Alpha ◽  
Cronbach's Alpha ◽  
Structured Report

Background: Structured reporting (SR) in radiology is becoming necessary and has recently been recognized by major scientific societies. This study aimed to build CT-based structured reports for lung cancer during the staging phase, in order to improve communication between radiologists, members of the multidisciplinary team and patients. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi exercise was used to build the structural report and to assess the level of agreement for all the report sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to perform a quality analysis according to the average inter-item correlation. Results: The final SR version was built by including 16 items in the “Patient Clinical Data” section, 4 items in the “Clinical Evaluation” section, 8 items in the “Exam Technique” section, 22 items in the “Report” section, and 5 items in the “Conclusion” section. Overall, 55 items were included in the final version of the SR. The overall mean of the scores of the experts and the sum of scores for the structured report were 4.5 (range 1–5) and 631 (mean value 67.54, STD 7.53), respectively, in the first round. The items of the structured report with higher accordance in the first round were primary lesion features, lymph nodes, metastasis and conclusions. The overall mean of the scores of the experts and the sum of scores for staging in the structured report were 4.7 (range 4–5) and 807 (mean value 70.11, STD 4.81), respectively, in the second round. The Cronbach’s alpha (Cα) correlation coefficient was 0.89 in the first round and 0.92 in the second round for staging in the structured report. Conclusions: The wide implementation of SR is critical for providing referring physicians and patients with the best quality of service, and for providing researchers with the best quality of data in the context of the big data exploitation of the available clinical data. Implementation is complex, requiring mature technology to successfully address pending user-friendliness, organizational and interoperability challenges.

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