55 research outputs found

    A concise revised myeloma comorbidity index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients

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    With growing numbers of elderly multiple myeloma patients, reliable tools to assess their vulnerability are required. The objective of the analysis herein was to develop and validate an easy to use myeloma risk score (revised Myeloma Comorbidity Index) that allows for risk prediction of overall survival and progression-free survival differences in a large patient cohort. We conducted a comprehensive comorbidity, frailty and disability evaluation in 801 consecutive myeloma patients, including comorbidity risks obtained at diagnosis. The cohort was examined within a training and validation set. Multivariate analysis determined renal, lung and Karnofsky Performance Status impairment, frailty and age as significant risks for overall survival. These were combined in a weighted revised Myeloma Comorbidity Index, allowing for the identification of fit (revised Myeloma Comorbidity Index ≤3 [n=247, 30.8%]), intermediate-fit (revised Myeloma Comorbidity Index 4-6 [n=446, 55.7%]) and frail patients (revised Myeloma Comorbidity Index >6 [n=108, 13.5%]): these subgroups, confirmed via validation analysis, showed median overall survival rates of 10.1, 4.4 and 1.2 years, respectively. The revised Myeloma Comorbidity Index was compared to other commonly used comorbidity indices (Charlson Comorbidity Index, Hematopoietic Cell Transplantation-Specific Comorbidity Index, Kaplan-Feinstein Index): if each were divided in risk groups based on 25% and 75% quartiles, highest hazard ratios, best prediction and Brier scores were achieved with the revised Myeloma Comorbidity Index. The advantages of the revised Myeloma Comorbidity Index include its accurate assessment of patients' physical conditions and simple clinical applicability. We propose the revised Myeloma Comorbidity Index to be tested with the “reference” International Myeloma Working Group frailty score in multicenter analyses and future clinical trials

    Evaluation of chemiluminescence, toluidine blue and histopathology for detection of high risk oral precancerous lesions: A cross-sectional study

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    <p>Abstract</p> <p>Background</p> <p>Early detection holds the key to an effective control of cancers in general and of oral cancers in particular. However, screening procedures for oral cancer are not straightforward due to procedural requirements as well as feasibility issues, especially in resource-limited countries.</p> <p>Methods</p> <p>We conducted a cross-sectional study to compare the performance of chemiluminescence, toluidine blue and histopathology for detection of high-risk precancerous oral lesions. We evaluated 99 lesions from 55 patients who underwent chemiluminescence and toluidine blue tests along with biopsy and histopathological examination. We studied inter-as well as intra-rater agreement in the histopathological evaluation and then using latent class modeling, we estimated the operating characteristics of these tests in the absence of a reference standard test.</p> <p>Results</p> <p>There was a weak inter-rater agreement (kappa < 0.15) as well as a weak intra-rater reproducibility (Pearson's r = 0.28, intra-class correlation rho = 0.03) in the histopathological evaluation of potentially high-risk precancerous lesions. When compared to histopathology, chemiluminescence and toluidine blue retention had a sensitivity of 1.00 and 0.59, respectively and a specificity of 0.01 and 0.79, respectively. However, latent class analysis indicated a low sensitivity (0.37) and high specificity (0.90) of histopathological evaluation. Toluidine blue had a near perfect high sensitivity and specificity for detection of high-risk lesions.</p> <p>Conclusion</p> <p>In our study, there was variability in the histopathological evaluation of oral precancerous lesions. Our results indicate that toluidine blue retention test may be better suited than chemiluminescence to detect high-risk oral precancerous lesions in a high-prevalence and low-resource setting like India.</p

    Evaluation of resource utilization and related cost

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