Comparison of CVD Risk Assessment via Qrisk®2 vs Reynolds Risk Score in Inflammatory Joint Diseases

Fatima, Fozia; Hakim, Farzana; Haq, Umer Ul; Shah, Muhammad Mehtab; Zeb, Fakhara Saba; Qasim, Muhammad; Khan, Shahbaz Ali; Fakhr, Amer; Manzar, Muhammad Adnan

doi:10.55519/jamc-04-10939

Cited by 2 publications

(3 citation statements)

References 22 publications

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“…However, studies show that mammography is not a perfect tool to detect breast cancer as it misses some tumors in some women, particularly in women at early ages, 13,14 and women with dense breasts. 9,13,14 The significance of combined mammographic and sonographic imaging in symptomatic patients has been previously studied. Also, the sensitivity of the two modalities on 45 participants was studied 9 , which resulted in 90.6% for mammography and 100% for U/S.…”

Section: Discussionmentioning

confidence: 99%

“…9,13,14 The significance of combined mammographic and sonographic imaging in symptomatic patients has been previously studied. Also, the sensitivity of the two modalities on 45 participants was studied 9 , which resulted in 90.6% for mammography and 100% for U/S. This figure was 77.7% for mammography and 55.5% for U/S.…”

Section: Discussionmentioning

confidence: 99%

“…7 Also, there are some limitations to doing mammography for women under the age 40-50 years old. 8,9 Over the last decade, most analogue mammography screening has changed into full field digital mammography (FFDM) which provides additional benefits for breast screening. 10 Digital mammography increases the detection rate and decreases the number of false positive leads, increasing the effectiveness of screening with sensitivity of over 85% and specificity over 90%.…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of Digital Mammography Unit in Diagnosis Breast Cancer in Gaza Strip, Palestine

AlShiekh¹,

Tawfeeq

Jabre³

2022

Arch Breast Cancer

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Background: Breast cancer is considered a major health problem and the most common cancer among females in both developed and non-developed countries. Early diagnosis of breast cancer decreases morbidities and mortalities. This study attempts to explore the accuracy measures of a digital mammography unit in the diagnosis of breast cancer and compare the mammography results with the final histopathology results. Methods: The study was designed as a cross-sectional prospective hospital base in which mammography examination was used for patients. Then, U/S was performed as a complementary study. All the mammography and U/S reports were reviewed and compared with the histopathology results. Six indicators were used to measure the accuracy of the mammography system using their formulas. SPSS program was used to examine the correlation between imaging results and histopathological findings and to draw the area under the receiver operating characteristic curve (AUC). Confidence interval was considered at 95% and margin of error at 5%. Results: Sensitivity, Specificity, PPV, NPV, accuracy and the area under the ROC curve of mammography alone were 94.9%, 66.7%, 90%, 66.7%, 0.771 and increased to 100%, 76.9%, 90.3%, 100%, 92.7%, 0.917, respectively when Ultrasound was used as a complementary to mammography. A statistically significant moderate correlation was shown between the results of mammography alone and histopathology results (Spearman correlation= 0.527, P-value<0.01), and a statistically significant strong correlation between mammography combined with ultrasound, and histopathology results (Spearman correlation=0.882, P-value<0.01). Conclusion: Mammography is an important tool to detect breast cancer. Mammography when combined with Ultrasound yields a very significant improvement in sensitivity and specificity for diagnosing different breast lesions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accuracy of Digital Mammography Unit in Diagnosis Breast Cancer in Gaza Strip, Palestine

AlShiekh¹,

Tawfeeq

Jabre³

2022

Arch Breast Cancer

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PREVENT Equation: The Black Sheep among Cardiovascular Risk Scores? A Comparative Agreement Analysis of Nine Prediction Models in High-Risk Lithuanian Women

Navickas,

Lukavičiūtė,

Glaveckaitė

et al. 2024

Medicina

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Background and Objectives: In the context of female cardiovascular risk categorization, we aimed to assess the inter-model agreement between nine risk prediction models (RPM): the novel Predicting Risk of cardiovascular disease EVENTs (PREVENT) equation, assessing cardiovascular risk using SIGN, the Australian CVD risk score, the Framingham Risk Score for Hard Coronary Heart Disease (FRS-hCHD), the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2). Materials and Methods: A cross-sectional study was conducted on 6527 40–65-year-old women with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the nine RPMs, and the results were categorized into high-, intermediate-, and low-risk groups. Inter-model agreement was quantified using Cohen’s Kappa coefficients. Results: The study uncovered a significant diversity in risk categorization, with agreement on risk category by all models in only 1.98% of cases. The SCORE2 model primarily classified subjects as high-risk (68.15%), whereas the FRS-hCHD designated the majority as low-risk (94.42%). The range of Cohen’s Kappa coefficients (−0.09–0.64) reflects the spectrum of agreement between models. Notably, the PREVENT model demonstrated significant agreement with QRISK3 (κ = 0.55) and PCE (κ = 0.52) but was completely at odds with the SCORE2 (κ = −0.09). Conclusions: Cardiovascular RPM selection plays a pivotal role in influencing clinical decisions and managing patient care. The PREVENT model revealed balanced results, steering clear of the extremes seen in both SCORE2 and FRS-hCHD. The highest concordance was observed between the PREVENT model and both PCE and QRISK3 RPMs. Conversely, the SCORE2 model demonstrated consistently low or negative agreement with other models, highlighting its unique approach to risk categorization. These findings accentuate the need for additional research to assess the predictive accuracy of these models specifically among the Lithuanian female population.

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Comparison of CVD Risk Assessment via Qrisk®2 vs Reynolds Risk Score in Inflammatory Joint Diseases

Cited by 2 publications

References 22 publications

Accuracy of Digital Mammography Unit in Diagnosis Breast Cancer in Gaza Strip, Palestine

Accuracy of Digital Mammography Unit in Diagnosis Breast Cancer in Gaza Strip, Palestine

PREVENT Equation: The Black Sheep among Cardiovascular Risk Scores? A Comparative Agreement Analysis of Nine Prediction Models in High-Risk Lithuanian Women

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