Yun-Jau Chang

Is quality of colorectal cancer care good enough? Core measures development and its application for comparing hospitals in Taiwan

BackgroundAlthough performance measurement for assessing care quality is an emerging area, a system for measuring the quality of cancer care at the hospital level has not been well developed. The purpose of this study was to develop organization-based core measures for colorectal cancer patient care and apply these measures to compare hospital performance.MethodsThe development of core measures for colorectal cancer has undergone three stages including a modified Delphi method. The study sample originated from 2004 data in the Taiwan Cancer Database, a national cancer data registry. Eighteen hospitals and 5585 newly diagnosed colorectal cancer patients were enrolled in this study. We used indicator-based and case-based approaches to examine adherences simultaneously.ResultsThe final core measure set included seventeen indicators (1 pre-treatment, 11 treatment-related and 5 monitoring-related). There were data available for ten indicators. Indicator-based adherence possesses more meaningful application than case-based adherence for hospital comparisons. Mean adherence was 85.8% (79.8% to 91%) for indicator-based and 82.8% (77.6% to 88.9%) for case-based approaches. Hospitals performed well (>90%) for five out of eleven indicators. Still, the performance across hospitals varied for many indicators. The best and poorest system performance was reflected in indicators T5-negative surgical margin (99.3%, 97.2% - 100.0%) and T7-lymph nodes harvest more than twelve(62.7%, 27.6% - 92.2%), both of which related to surgical specimens.ConclusionsIn this nationwide study, quality of colorectal cancer care still shows room for improvement. These preliminary results indicate that core measures for cancer can be developed systematically and applied for internal quality improvement.

Risk groups defined by Recursive Partitioning Analysis of patients with colorectal adenocarcinoma treated with colorectal resection

BackgroundTo define different prognostic groups of surgical colorectal adenocarcinoma patients derived from recursive partitioning analysis (RPA).MethodsTen thousand four hundred ninety four patients with colorectal adenocarcinoma underwent colorectal resection from Taiwan Cancer Database during 2003 to 2005 were included in this study. Exclusion criteria included those patients with stage IV disease or without number information of lymph nodes. For the definition of risk groups, the method of classification and regression tree was performed. Main primary outcome was 5-year cancer-specific survival.ResultsWe identified six prognostic factors for cancer-specific survival, resulting in seven terminal nodes. Four risk groups were defined as following: Group 1 (mild risk, 1,698 patients), Group 2 (moderate risk, 3,129 patients), Group 3 (high risk, 4,605 patients) and Group 4 (very high risk, 1,062 patients). The 5-year cancer-specific survival for Group 1, 2, 3, and 4 was 86.6%, 62.7%, 55.9%, and 36.6%, respectively (p < 0.001). Hazard ratio of death was 2.13, 5.52 and 10.56 (95% confidence interval 1.74-2.60, 4.58-6.66 and 8.66-12.9, respectively) times for Group 2, 3, and 4 as compared to Group 1. The predictive capability of these grouping was also similar in terms of overall and progression-free survival.ConclusionThe use of RPA offered an alternative grouping method that could predict the survival of patients who underwent surgery for colorectal adenocarcinoma.

Ratio and log odds of positive lymph nodes in breast cancer patients with mastectomy

PURPOSE This study aimed to investigate the predictive role of lymph nodes (LNs) and assess the prognostic significance of the ratio of positive LNs (LNR) and log odds of positive LNs (LODDS) in breast cancer patients who have undergone a mastectomy. PATIENTS AND METHODS All of the breast cancer patients in the Taiwan Cancer Database during 2002-2006 were considered. We excluded patients who had inflammatory breast cancer, stage 0 and IV disease, breast conservative surgery or survival <1 month. The primary end point was overall survival (OS). A Cox hazards model was constructed and compared via Nagelkerke R(2) (R(2)N) and receiver operating characteristics (ROC). RESULTS A total of 11,349 (6042 node-negative, 5307 node-positive) patients were enrolled, and 10.5% patients had a limited number of LNs harvested. In a multivariate Cox model, LNR and LODDS demonstrated prognostic significance (<0.001). For node-positive patients, a model with LNR showed the best fit (P < 0.001; R(2)N = 18.2%) when sufficient LNs were examined. However, a model with LODDS showed the best fit in patients with a limited number of LNs harvested (P < 0.001; R(2)N = 21.1%), even in node-negative patients (P = 0.004; R(2)N = 13.5%). The area under the ROC curve (AUC) was highest for LODDS (AUC: 0.761), followed by LNR (AUC: 0.757). A limited LN harvest induced an AUC value for an approximate 3.6% loss (LNR) or 3.1% loss (LODDS). CONCLUSION The prognostic superiority of LNR is confounded by a limited LN harvest, thus making LODDS the most powerful and unified prognostic classifier in breast cancer patients who have had a mastectomy.

Application of propensity score model to examine the prognostic significance of lymph node number as a care quality indicator

PURPOSE There is a controversy about whether lymph node yield can be used as a proxy of quality care for patient with colorectal cancer. We aim to use propensity score models to investigate the association between lymph node number and long-term survival for colorectal cancer patients. MATERIALS AND METHODS Taiwan Cancer Database was employed to review all patients with newly diagnosed colorectal cancer from 2003 to 2005. Exclusion criteria included those patients with stage IV disease or without information of lymph node. Propensity score models (examined lymph node >12 or <12 as dependent variable) were applied to group of patients with Stage II or Stage III disease and primary end point was 5-year survival (and mortality). We also report results of Stage I-III for comparison. RESULTS We identified 15,731 newly diagnosed colorectal cancers during study period, among which a total of 10,517 colorectal cancer patients treated at 32 hospitals fulfilled the inclusion criteria. Pathology reports of about 63 % (6658/10517) patients revealed lymph node retrieval >12. After propensity score matching, there were 2888, 1079, 1094 pairs recruited for Stage I-III, Stage II and Stage III, respectively. According to analysis of these matched pairs, the 5-year risk adjusted overall mortality were lower for lymph node examined ≥12 than <12 among Stage II (24.3% vs. 31.1%, p=0.012) and Stage I-III (20.8% vs. 23.6%, p=0.003), but insignificant for Stage III (40.2% vs. 45.6%, p=0.073). Similar situation happened with regard to disease-free and disease-specific mortality. CONCLUSION For patients with colorectal cancer undergoing colorectal surgery, the quality metric of lymph node is associated with significantly better 5-year survival except for Stage III disease.

Statistical process control as a tool for controlling operating room performance: retrospective analysis and benchmarking

BACKGROUND There is much research using statistical process control (SPC) to monitor surgical performance, including comparisons among groups to detect small process shifts, but few of these studies have included a stabilization process. This study aimed to analyse the performance of surgeons in operating room (OR) and set a benchmark by SPC after stabilized process. METHODS The OR profile of 499 patients who underwent laparoscopic cholecystectomy performed by 16 surgeons at a tertiary hospital in Taiwan during 2005 and 2006 were recorded. SPC was applied to analyse operative and non-operative times using the following five steps: first, the times were divided into two segments; second, they were normalized; third, they were evaluated as individual processes; fourth, the ARL(0) was calculated;, and fifth, the different groups (surgeons) were compared. Outliers were excluded to ensure stability for each group and to facilitate inter-group comparison. RESULTS The results showed that in the stabilized process, only one surgeon exhibited a significantly shorter total process time (including operative time and non-operative time). CONCLUSION In this study, we use five steps to demonstrate how to control surgical and non-surgical time in phase I. There are some measures that can be taken to prevent skew and instability in the process. Also, using SPC, one surgeon can be shown to be a real benchmark.

Long-term survival of patients undergoing liver resection for very large hepatocellular carcinomas.

This study aimed to assess long‐term survival after liver resection for huge hepatocellular carcinoma (HCC).

Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients

AbstractLymph node ratio (LNR) is a powerful prognostic factor for breast cancer. We conducted a recursive partitioning analysis (RPA) of the LNR to identify the prognostic risk groups in breast cancer patients. Records of newly diagnosed breast cancer patients between 2002 and 2006 were searched in the Taiwan Cancer Database. The end of follow-up was December 31, 2009. We excluded patients with distant metastases, inflammatory breast cancer, survival <1 month, no mastectomy, or missing lymph node status. Primary outcome was 5-year overall survival (OS). For univariate significant predictors, RPA were used to determine the risk groups. Among the 11,349 eligible patients, we identified 4 prognostic factors (including LNR) for survival, resulting in 8 terminal nodes. The LNR cutoffs were 0.038, 0.259, and 0.738, which divided LNR into 4 categories: very low (LNR ⩽ 0.038), low (0.038 < LNR ⩽ 0.259), moderate (0.259 < LNR ⩽ 0.738), and high (0.738 < LNR). Then, 4 risk groups were determined as follows: Class 1 (very low risk, 8,265 patients), Class 2 (low risk, 1,901 patients), Class 3 (moderate risk, 274 patients), and Class 4 (high risk, 900 patients). The 5-year OS for Class 1, 2, 3, and 4 were 93.2%, 83.1%, 72.3%, and 56.9%, respectively (P< 0.001). The hazard ratio of death was 2.70, 4.52, and 8.59 (95% confidence interval 2.32–3.13, 3.49–5.86, and 7.48–9.88, respectively) times for Class 2, 3, and 4 compared with Class 1 (P < 0.001). In conclusion, we identified the optimal cutoff LNR values based on RPA and determined the related risk groups, which successfully predict 5-year OS in breast cancer patients.

Can composite performance measures predict survival of patients with colorectal cancer

AIM To assess the relationship between long-term colorectal patient survival and methods of calculating composite performance scores. METHODS The Taiwan Cancer Database was used to identify patients who underwent bowel resection for colorectal adenocarcinoma between 2003 and 2004. Patients were assigned to one of three cohorts based on tumor staging: cohort 1, colon cancer stage < III; cohort 2, colon cancer stage III; cohort 3, rectal cancer. A composite performance score (CPS) was calculated for each patient using five different aggregating methods, including all-or-none, 70% standard, equal weight, analytic hierarchy process (AHP), and principal component analysis (PCA) algorithms. The relationships between CPS and five-year overall, disease-free, and disease-specific survivals were evaluated by a Cox proportional hazards model. A goodness-of-fit analysis for all five methods was performed using Akaikes information criterion. RESULTS A total of 3272 colorectal cancer patients (cohort 1, 1164; cohort 2, 790; cohort 3, 1318 patients) with a mean age of 65 years were enrolled in the study. Bivariate correlation analysis showed that CPS values from the equal weight method were highly correlated with those from the AHP method in all cohorts (all P < 0.05). Multivariate Cox hazards analysis showed that CPS values derived from equal weight and AHP methods were significantly associated with five-year survivals of patients in cohorts 1 and 2 (all P < 0.05). In these cohorts, higher CPS values suggested a higher probability of five-year survival. However, CPS values derived from the all-or-none method did not show any significant process-outcome relationship in any cohort. Goodness-of-fit analyses showed that CPS values derived from the PCA method were the best fit to the Cox proportional hazards model, whereas the values from the all-or-none model showed the poorest fit. CONCLUSION CPS values may highlight process-outcome relationships for patients with colorectal cancer in addition to evaluating quality of care performance.