Risk factors to predict the incidence of surgical adverse events following open or laparoscopic surgery for apparent early stage endometrial cancer: results from a randomised controlled trial

Aims: To identify risk factors for major Adverse Events (AEs) and to develop a nomogram to predict the probability of such AEs in individual patients who have surgery for apparent early stage endometrial cancer. Methods: We used data from 753 patients who were randomized to either total laparoscopic hysterectomy or total abdominal hysterectomy in the LACE trial. Serious adverse events that prolonged hospital stay or postoperative adverse events (using common terminology criteria 3+, CTCAE V3) were considered major AEs. We analyzed pre-surgical characteristics that were associated with the risk of developing major AEs by multivariate logistic regression. We identified a parsimonious model by backward stepwise logistic regression. The six most significant or clinically important variables were included in the nomogram to predict the risk of major AEs within 6 weeks of surgery and the nomogram was internally validated. Results: Overall, 132 (17.5%) patients had at least one major AE. An open surgical approach (laparotomy), higher Charlson’s medical co-morbidities score, moderately differentiated tumours on curettings, higher baseline ECOG score, higher body mass index and low haemoglobin levels were associated with AE and were used in the nomogram. The bootstrap corrected concordance index of the nomogram was 0.63 and it showed good calibration. Conclusions: Six pre-surgical factors independently predicted the risk of major AEs. This research might form the basis to develop risk reduction strategies to minimize the risk of AEs among patients undergoing surgery for apparent early stage endometrial cancer.

Honesty about adverse events - more honoured in the breach than in the observance

The medical board of Australia Code of conduct reminds doctors that" "When adverse events occur, you have a responsibility to be open and honest in your communication with your patient, to review what has occurred and to report appropriately." More honoured in the breach rather than the observence may or may not be correct. Faced with the English concerns and the Netherlands research, an evidence based assessment of compliance with the ethical duty to disclose adverse events is warranted.

Sequential monitoring of hospital adverse events when control charts fail : the example of fall injuries in hospitals

Objective To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation. Design Retrospective audit. Setting The Northern Hospital, Melbourne, Australia. Participants 171,059 patients admitted between January 2001 and December 2006. Measurements The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit. Results The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation. Conclusion Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.

A systematic review of patient-reported outcome instruments of dermatologic adverse events associated with targeted cancer therapies

Purpose Dermatologic adverse events (dAEs) in cancer treatment are frequent with the use of targeted therapies. These dAEs have been shown to have significant impact on health-related quality of life (HRQoL). While standardized assessment tools have been developed for physicians to assess severity of dAEs, there is a discord between objective and subjective measures. The identification of patient-reported outcome (PRO) instruments useful in the context of targeted cancer therapies is therefore important in both the clinical and research settings for the overall evaluation of dAEs and their impact on HRQoL. Methods A comprehensive, systematic literature search of published articles was conducted by two independent reviewers in order to identify PRO instruments previously utilized in patient populations with dAEs from targeted cancer therapies. The identified PRO instruments were studied to determine which HRQoL issues relevant to dAEs were addressed, as well as the process of development and validation of these instruments. Results Thirteen articles identifying six PRO instruments met the inclusion criteria. Four instruments were general dermatology (Skindex-16©, Skindex-29©, Dermatology Life Quality Index (DLQI), and DIELH-24) and two were symptom-specific (functional assessment of cancer therapy-epidermal growth factor receptor inhibitor-18 (FACT-EGFRI-18) and hand-foot syndrome-14 (HFS-14)). Conclusions While there are several PRO instruments that have been tested in the context of targeted cancer therapy, additional work is needed to develop new instruments and to further validate the instruments identified in this study in patients receiving targeted therapies.

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

Lower preoperative quality of life increases postoperative risk of adverse events in women with endometrial cancer: results from the LACE trial

Objective: To examine the association between preoperative quality of life (QoL) and postoperative adverse events in women treated for endometrial cancer. Methods: 760 women with apparent Stage I endometrial cancer were randomised into a clinical trial evaluating laparoscopic versus open surgery. This analysis includes women with preoperative QoL measurements, from the Functional Assessment of Cancer Therapy- General (FACT-G) questionnaire, and who were followed up for at least 6 weeks after surgery (n=684). The outcomes for this study were defined as (1) the occurrence of moderate to severe AEs adverse events within 6 months (Common Toxicology Criteria (CTC) grade ≥3); and (2) any Serious Adverse Event (SAE). The association between preoperative QoL and the occurrence of AE was examined, after controlling for baseline comorbidity and other factors. Results: After adjusting for other factors, odds of occurrence of AE of CTC grade ≥3 were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.00-1.03, p=0.030), which was driven by physical well-being (PWB) (OR=1.09, 95% CI 1.04-1.13, p=0.0002) and functional well-being subscales (FWB) (OR=1.04, 95% CI 1.00-1.07, p=0.035). Similarly, odds of SAE occurrence were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.01-1.04, p=0.011), baseline PWB (OR=1.11, 95% CI 1.06-1.16, p<0.0001) or baseline FWB subscales (OR=1.05, 95% CI 1.01-1.10, p=0.0077). Conclusion: Women with early endometrial cancer presenting with lower QoL prior to surgery are at higher risk of developing a serious adverse event following surgery. Funding: Cancer Council Queensland, Cancer Council New South Wales, Cancer Council Victoria, Cancer Council, Western Australia; NHMRC project grant 456110; Cancer Australia project grant 631523; The Women and Infants Research Foundation, Western Australia; Royal Brisbane and Women’s Hospital Foundation; Wesley Research Institute; Gallipoli Research Foundation; Gynetech; TYCO Healthcare, Australia; Johnson and Johnson Medical, Australia; Hunter New England Centre for Gynaecological Cancer; Genesis Oncology Trust; and Smart Health Research Grant QLD Health.

Detecting Adverse Events in Clinical Trial Free Text

Thesis (Master's)--University of Washington, 2013

Predicting adverse events in children with fever and chemotherapy-induced neutropenia: the prospective multicenter SPOG 2003 FN study.

PURPOSE To develop a score predicting the risk of adverse events (AEs) in pediatric patients with cancer who experience fever and neutropenia (FN) and to evaluate its performance. PATIENTS AND METHODS Pediatric patients with cancer presenting with FN induced by nonmyeloablative chemotherapy were observed in a prospective multicenter study. A score predicting the risk of future AEs (ie, serious medical complication, microbiologically defined infection, radiologically confirmed pneumonia) was developed from a multivariate mixed logistic regression model. Its cross-validated predictive performance was compared with that of published risk prediction rules. Results An AE was reported in 122 (29%) of 423 FN episodes. In 57 episodes (13%), the first AE was known only after reassessment after 8 to 24 hours of inpatient management. Predicting AE at reassessment was better than prediction at presentation with FN. A differential leukocyte count did not increase the predictive performance. The score predicting future AE in 358 episodes without known AE at reassessment used the following four variables: preceding chemotherapy more intensive than acute lymphoblastic leukemia maintenance (weight = 4), hemoglobin > or = 90 g/L (weight = 5), leukocyte count less than 0.3 G/L (weight = 3), and platelet count less than 50 G/L (weight = 3). A score (sum of weights) > or = 9 predicted future AEs. The cross-validated performance of this score exceeded the performance of published risk prediction rules. At an overall sensitivity of 92%, 35% of the episodes were classified as low risk, with a specificity of 45% and a negative predictive value of 93%. CONCLUSION This score, based on four routinely accessible characteristics, accurately identifies pediatric patients with cancer with FN at risk for AEs after reassessment.