Cancer staging determines extent of disease, facilitating prognostication and treatment decision making. The American Joint Committee on Cancer (AJCC) TNM classification system is the most commonly ...used staging algorithm for colon cancer, categorizing patients on the basis of only these three variables (tumor, node, and metastasis). The purpose of this study was to extend the seventh edition of the AJCC staging system for colon cancer to incorporate additional information available from tumor registries, thereby improving prognostic accuracy.
Records from 128,853 patients with primary colon cancer reported to the Surveillance, Epidemiology and End Results Program from 1994 to 2005 were used to construct and validate three survival models for patients with primary curative-intent surgery. Independent training/test data sets were used to develop and test alternative models. The seventh edition TNM staging system was compared with models supplementing TNM staging with additional demographic and tumor variables available from the registry by calculating a concordance index, performing calibration, and identifying the area under receiver operating characteristic (ROC) curves.
Inclusion of additional registry covariates improved prognostic estimates. The concordance index rose from 0.60 (95% CI, 0.59 to 0.61) for the AJCC model, with T- and N-stage variables, to 0.68 (95% CI, 0.67 to 0.68) for the model including tumor grade, number of collected metastatic lymph nodes, age, and sex. ROC curves for the extended model had higher sensitivity, at all values of specificity, than the TNM system; calibration curves indicated no deviation from the reference line.
Prognostic models incorporating readily available data elements outperform the current AJCC system. These models can assist in personalizing treatment and follow-up for patients with colon cancer.
Pantalone et al. discussed the evidence of clinical inertia in type 2 diabetes (T2D) management according to a large, real-world data set. A systematic review revealed that the median time to ...treatment intensification after HbA1c measurement above target was longer than 1 year. They previously reported a rather high rate of clinical inertia in patients uncontrolled of metformin monotherapy, in which treatment was not intensified early. They noted that the real-world findings confirmed a high prevalence of clinical inertia with regard to T2D management. The data suggested that physicians are not responding quickly enough to evidence of poor glycemic control in a high percentage of patients.
Purpose PCA3 is a urinary marker that has shown promise in predicting the presence of prostate cancer in men undergoing repeat prostate biopsy. We studied PCA3 before initial prostate biopsy. ...Materials and Methods Records from a single organization were retrospectively reviewed. The predictive value of PCA3 was explored using nonparametric receiver operating characteristic curve analysis (ROC) and multivariable logistic regression analysis. Results A total of 3,073 men underwent PCA3 analysis before initial prostate biopsy sampling of 12 to 14 areas. Mean PCA3 was 27.2 and 52.5 for patients without and with cancer, respectively. Prostate cancer was identified in 1,341 (43.6%) men. Overall 54.5% had Gleason 6 disease and 45.5% had Gleason 7 or greater (high grade prostate cancer). Mean PCA3 was 47.5 and 58.5 for the patients with Gleason 6 and 7 or greater disease, respectively. On multivariable logistic analysis PCA3 was statistically significantly associated with prostate cancer and high grade prostate cancer after adjusting for prostate specific antigen (p <0.001 for both), free prostate specific antigen (p = 0.04 and p = 0.01, respectively), age (p <0.001 for both), family history (p <0.001 and p = 0.59, respectively), abnormal digital rectal examination (p = 0.31 and p <0.001, respectively), prostate volume (p <0.001 for both) and body mass index (p <0.001 for both). Using ROC analysis PCA3 outperformed prostate specific antigen in the prediction of prostate cancer (AUC 0.697 vs 0.599, p <0.01) but not for high grade prostate cancer (AUC 0.682 vs 0.679, p = 0.702). Conclusions PCA3 proved a useful tool in identifying patients at risk for prostate cancer before initial prostate biopsy. To our knowledge this is the largest PCA3 study in the initial biopsy population. These results suggest that further exploration of the value of PCA3 is warranted.
Purpose: Accurate estimates of risk are essential for physicians if they are to recommend a specific management to patients with prostate
cancer. Accurate risk estimates are also required for ...clinical trial design, to ensure homogeneous patient groups. Because
there is more than one model available for prediction of most outcomes, model comparisons are necessary for selection of the
best model. We describe the criteria based on which to judge predictive tools, describe the limitations of current predictive
tools, and compare the different predictive methodologies that have been used in the prostate cancer literature.
Experimental Design: Using MEDLINE, a literature search was done on prostate cancer decision aids from January 1966 to July 2007.
Results: The decision aids consist of nomograms, risk groupings, artificial neural networks, probability tables, and classification
and regression tree analyses. The following considerations need to be applied when the qualities of predictive models are
assessed: predictive accuracy (internal or ideally external validation), calibration (i.e., performance according to risk
level or in specific patient subgroups), generalizability (reproducibility and transportability), and level of complexity
relative to established models, to assess whether the new model offers advantages relative to available alternatives. Studies
comparing decision aids have shown that nomograms outperform the other methodologies.
Conclusions: Nomograms provide superior individualized disease-related risk estimations that facilitate management-related decisions.
Of currently available prediction tools, the nomograms have the highest accuracy and the best discriminating characteristics
for predicting outcomes in prostate cancer patients.
Eur J Clin Invest 2011
Background New markers may improve prediction of diagnostic and prognostic outcomes. We review various measures to quantify the incremental value of markers over standard, ...readily available characteristics.
Methods Widely used traditional measures include the improvement in model fit or in the area under the receiver operating characteristic (ROC) curve (AUC). New measures include the net reclassification index (NRI) and decision‐analytic measures, such as the fraction of true‐positive classifications penalized for false‐positive classifications net benefit (NB). For illustration, we discuss a case study on the presence of residual tumour vs. benign tissue in 544 patients with testicular cancer. We assessed three tumour markers Alpha‐fetoprotein (AFP), Human chorionic gonadotropin (HCG) and Lactate dehydrogenase (LDH) for their incremental value over currently standard clinical predictors.
Results AUC and R2 values suggested adding continuous LDH and AFP whereas NB only favoured HCG as a potentially promising marker at a clinically defendable decision threshold of 20% risk. The NRI suggested reclassification potential of all three markers.
Conclusions The improvement in standard discrimination measures, which focus on finding variables that might be promising across all decision thresholds, may not detect the most informative markers at a specific threshold of particular clinical relevance. When a marker is intended to support decision‐making, calculation of the improvement in a decision‐analytic measure, such as NB, is preferable over an overall judgment as obtained from the AUC in ROC analysis.
Purpose Laparoscopic partial nephrectomy is an increasingly performed, minimally invasive alternative to open partial nephrectomy. We compared early postoperative outcomes in 1,800 patients ...undergoing open partial nephrectomy by experienced surgeons with the initial experience with laparoscopic partial nephrectomy in patients with a single renal tumor 7 cm or less. Materials and Methods Data on 1,800 consecutive open or laparoscopic partial nephrectomies were collected prospectively or retrospectively in tumor registries at 3 large referral centers. Demographic, intraoperative, postoperative and followup data were compared between the 2 groups. Results Compared to the laparoscopic partial nephrectomy group of 771 patients the 1,028 undergoing open partial nephrectomy were a higher risk group with a greater percent presenting symptomatically with decreased performance status, impaired renal function and tumor in a solitary functioning kidney (p <0.0001). More tumors in the open partial nephrectomy group were more than 4 cm and centrally located and more proved to be malignant (p <0.0001 and 0.0003, respectively). Based on multivariate analysis laparoscopic partial nephrectomy was associated with shorter operative time (p <0.0001), decreased operative blood loss (p <0.0001) and shorter hospital stay (p <0.0001). The chance of intraoperative complications was comparable in the 2 groups. However, laparoscopic partial nephrectomy was associated with longer ischemia time (p <0.0001), more postoperative complications, particularly urological (p <0.0001), and an increased number of subsequent procedures (p <0.0001). Renal functional outcomes were similar 3 months after laparoscopic and open partial nephrectomy with 97.9% and 99.6% of renal units retaining function, respectively. Three-year cancer specific survival for patients with a single cT1N0M0 renal cell carcinoma was 99.3% and 99.2% after laparoscopic and open partial nephrectomy, respectively. Conclusions Early experience with laparoscopic partial nephrectomy is promising. Laparoscopic partial nephrectomy offered the advantages of less operative time, decreased operative blood loss and a shorter hospital stay. When applied to patients with a single renal tumor 7 cm or less, laparoscopic partial nephrectomy was associated with additional postoperative morbidity compared to open partial nephrectomy. However, equivalent functional and early oncological outcomes were achieved.
We have entered the era of “big data” and with that the explosion of interest in prediction modeling. With this explosion comes the challenge of evaluating statistical prediction models, both from ...the standpoint of an author as well as a reviewer. This article provides guidance for the evaluation and critique of a statistical prediction model. Hopefully, this will improve the quality of statistical prediction modeling studies and facilitate their review.
IMPORTANCE: Obesity is an established risk factor for severe COVID-19 infection. However, it is not known whether losing weight is associated with reduced adverse outcomes of COVID-19 infection. ...OBJECTIVE: To investigate the association between a successful weight loss intervention and improved risk and severity of COVID-19 infection in patients with obesity. DESIGN, SETTING, AND PARTICIPANTS: This cohort study involved adult patients with a body mass index of 35 or higher (calculated as weight in kilograms divided by height in meters squared) who underwent weight loss surgery between January 1, 2004, and December 31, 2017, at the Cleveland Clinic Health System (CCHS). Patients in the surgical group were matched 1:3 to patients who did not have surgical intervention for their obesity (control group). The source of data was the CCHS electronic health record. Follow-up was conducted through March 1, 2021. EXPOSURES: Weight loss surgery including Roux-en-Y gastric bypass and sleeve gastrectomy. MAIN OUTCOMES AND MEASURES: Distinct outcomes were examined before and after COVID-19 outbreak on March 1, 2020. Weight loss and all-cause mortality were assessed between the enrollment date and March 1, 2020. Four COVID-19–related outcomes were analyzed in patients with COVID-19 diagnosis between March 1, 2020, and March 1, 2021: positive SARS-CoV-2 test result, hospitalization, need for supplemental oxygen, and severe COVID-19 infection (a composite of intensive care unit admission, need for mechanical ventilation, or death). RESULTS: A total of 20 212 patients (median IQR age, 46 35-57 years; 77.6% female individuals 15 690) with a median (IQR) body mass index of 45 (41-51) were enrolled. The overall median (IQR) follow-up duration was 6.1 (3.8-9.0) years. Before the COVID-19 outbreak, patients in the surgical group compared with control patients lost more weight (mean difference at 10 years from baseline: 18.6 95% CI, 18.4-18.7 percentage points; P < .001) and had a 53% lower 10-year cumulative incidence of all-cause non–COVID-19 mortality (4.7% 95% CI, 3.7%-5.7% vs 9.4% 95% CI, 8.7%-10.1%; P < .001). Of the 20 212 enrolled patients, 11 809 were available on March 1, 2020, for an assessment of COVID-19–related outcomes. The rates of positive SARS-CoV-2 test results were comparable in the surgical and control groups (9.1% 95% CI, 7.9%-10.3% vs 8.7% 95% CI, 8.0%-9.3%; P = .71). However, undergoing weight loss surgery was associated with a lower risk of hospitalization (adjusted hazard ratio HR, 0.51; 95% CI, 0.35-0.76; P < .001), need for supplemental oxygen (adjusted HR, 0.37; 95% CI, 0.23-0.61; P < .001), and severe COVID-19 infection (adjusted HR, 0.40; 95% CI, 0.18-0.86; P = .02). CONCLUSIONS AND RELEVANCE: This cohort study found that, among patients with obesity, substantial weight loss achieved with surgery was associated with improved outcomes of COVID-19 infection. The findings suggest that obesity can be a modifiable risk factor for the severity of COVID-19 infection.
Despite advances in cancer genomics, radiotherapy is still prescribed on the basis of an empirical one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic-adjusted ...radiation dose (GARD) model to personalise prescription of radiation dose on the basis of the biological effect of a given physical dose of radiation, calculated using individual tumour genomics. We hypothesise that GARD will reveal interpatient heterogeneity associated with opportunities to improve outcomes compared with physical dose of radiotherapy alone. We aimed to test this hypothesis and investigate the GARD-based radiotherapy dosing paradigm.
We did a pooled, pan-cancer analysis of 11 previously published clinical cohorts of unique patients with seven different types of cancer, which are all available cohorts with the data required to calculate GARD, together with clinical outcome. The included cancers were breast cancer, head and neck cancer, non-small-cell lung cancer, pancreatic cancer, endometrial cancer, melanoma, and glioma. Our dataset comprised 1615 unique patients, of whom 1298 (982 with radiotherapy, 316 without radiotherapy) were assessed for time to first recurrence and 677 patients (424 with radiotherapy and 253 without radiotherapy) were assessed for overall survival. We analysed two clinical outcomes of interest: time to first recurrence and overall survival. We used Cox regression, stratified by cohort, to test the association between GARD and outcome with separate models using dose of radiation and sham-GARD (ie, patients treated without radiotherapy, but modelled as having a standard-of-care dose of radiotherapy) for comparison. We did interaction tests between GARD and treatment (with or without radiotherapy) using the Wald statistic.
Pooled analysis of all available data showed that GARD as a continuous variable is associated with time to first recurrence (hazard ratio HR 0·98 95% CI 0·97–0·99; p=0·0017) and overall survival (0·97 0·95–0·99; p=0·0007). The interaction test showed the effect of GARD on overall survival depends on whether or not that patient received radiotherapy (Wald statistic p=0·011). The interaction test for GARD and radiotherapy was not significant for time to first recurrence (Wald statistic p=0·22). The HR for physical dose of radiation was 0·99 (95% CI 0·97–1·01; p=0·53) for time to first recurrence and 1·00 (0·96–1·04; p=0·95) for overall survival. The HR for sham-GARD was 1·00 (0·97–1·03; p=1·00) for time to first recurrence and 1·00 (0·98–1·02; p=0·87) for overall survival.
The biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose.
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