Collecting Long-Term Outcomes in Population-Based Cancer Registry Data: The Case of Breast Cancer Recurrence

PURPOSE

Cancer recurrence is an important long-term outcome of cancer survivors that is often not routinely collected and recorded by population-based registries. In this study, we review population-based studies to determine the current availability, landscape, and infrastructure of long-term outcomes, particularly metastatic recurrence, in women initially diagnosed with nonmetastatic breast cancer (MBC).

METHODS

We reviewed the literature to identify studies that used population-based registry data to examine the distribution of metastatic recurrence in women diagnosed with non-MBC. Data on outcomes and methods of ascertainment were extracted. Registry infrastructure including sources and funding was also reviewed.

RESULTS

A total of 23 studies from 11 registries in eight countries spanning Europe, North America, and Oceania were identified and included in the review. Most studies were retrospective in nature and collected recurrence data only for ad hoc studies rather than as part of their routine registration. Definition of recurrence and data sources varied considerably across studies: the cancer-free time interval between the start of follow-up and risk window ranged from the diagnosis of primary tumor (n = 7) to 6 months from diagnosis (n = 1); the start of follow-up differed between initial diagnosis (n = 16) and treatment (n = 7).

CONCLUSION

Cancer surveillance should encompass outcomes among survivors for research and monitoring. Studies are underway, but more are needed. Cancer registries should be supported to routinely collect recurrence data to allow complete evaluation of MBC as an outcome to be conducted and inform health care providers and researchers of the prognosis of both nonmetastatic and metastatic patients with breast cancer.

Tumor size improves the accuracy of the prognostic prediction of T4a stage colon cancer

The aim of this study was to evaluate the potential impact of tumor size on the long-term outcome of colon cancer (CC) patients after curative surgery. A total of 782 curatively resected T4a stage CC patients without distant metastasis were enrolled. Patients were categorized into 2 groups according to the best threshold of tumor size: larger group (LG) and smaller group (SG). Propensity score matching was used to adjust for the differences in baseline characteristics. The ideal cutoff point of tumor size was 5 cm. In the multivariate analysis for the whole study series, tumor size was an independent prognostic factor. Patients in the LG had significant lower 5-year overall survival (OS) and relapse-free survival (RFS) rates (OS: 63.5% versus 75.2%, P < 0.001; RFS: 59.5% versus 72.4%, P < 0.001) than those in the SG. After matching, patients in the LG still demonstrated significant lower 5-year OS and RFS rates than those in the SG. The modified tumor-size-node-metastasis (mTSNM) staging system including tumor size was found to be more appropriate for predicting the OS and RFS of T4a stage CC than TNM stage, and the -2log likelihood of the mTSNM staging system was smaller than the value of TNM stage. In conclusion, tumor size was an independent prognostic factor for OS and RFS. We maintain that tumor size should be incorporated into the staging system to enhance the accuracy of the prognostic prediction of T4a stage CC patients.

Evaluating the Age-Based Recommendations for Long-Term Follow-Up in Breast Cancer

BACKGROUND

After 5 years of annual follow-up following breast cancer, Dutch guidelines are age based: annual follow-up for women <60 years, 60-75 years biennial, and none for >75 years. We determined how the risk of recurrence corresponds to these consensus-based recommendations and to the risk of primary breast cancer in the general screening population.

SUBJECTS, MATERIALS, AND METHODS

Women with early-stage breast cancer in 2003/2005 were selected from the Netherlands Cancer Registry (n = 18,568). Cumulative incidence functions were estimated for follow-up years 5-10 for locoregional recurrences (LRRs) and second primary tumors (SPs). Risks were compared with the screening population without history of breast cancer. Alternative cutoffs for age were determined by log-rank tests.

RESULTS

The cumulative risk for LRR/SP was lower in women <60 years (5.9%, 95% confidence interval [CI] 5.3-6.6) who are under annual follow-up than for women 60-75 (6.3%, 95% CI 5.6-7.1) receiving biennial visits. All risks were higher than the 5-year risk of a primary tumor in the screening population (ranging from 1.4% to 1.9%). Age cutoffs <50, 50-69, and > 69 revealed better risk differentiation and would provide more risk-based schedules. Still, other factors, including systemic treatments, had an even greater impact on recurrence risks.

CONCLUSION

The current consensus-based recommendations use suboptimal age cutoffs. The proposed alternative cutoffs will lead to a more balanced risk-based follow-up and thereby more efficient allocation of resources. However, more factors should be taken into account for truly individualizing follow-up based on risk for recurrence.

IMPLICATIONS FOR PRACTICE

The current age-based recommendations for breast cancer follow-up after 5 years are suboptimal and do not reflect the actual risk of recurrent disease. This results in situations in which women with higher risks actually receive less follow-up than those with a lower risk of recurrence. Alternative cutoffs could be a start toward risk-based follow-up and thereby more efficient allocation of resources. However, age, or any single risk factor, is not able to capture the risk differences and therefore is not sufficient for determining follow-up. More risk factors should be taken into account for truly individualizing follow-up based on the risk for recurrence.

Novel prognostic nomograms for female patients with breast cancer and bone metastasis at presentation

Background

There is a paucity of literature about prognostic evaluation for patients with breast cancer (BC) and bone metastasis at presentation. To date, little is known about how to accurately predict the prognosis of BC patients with bone metastasis at presentation. Thus, an accurate prediction tool of prognosis in this population is urgently needed. Our goal is to construct novel and prognostic nomograms for BC patients with bone metastasis at presentation.

Methods

We searched Surveillance, Epidemiology, and End Results (SEER) database for BC patients with bone metastasis at presentation between 2010 and 2016. Multivariate analysis was performed to obtain significantly independent variables. Then, novel prognostic nomograms were constructed based on those independent predictors.

Results

Tumor grade, histological type, primary tumor size, tumor subtype, surgery, chemotherapy and number of metastatic organs except bone were recognized as significantly independent variables of both overall survival (OS) and cancer-specific survival (CSS). Then those significant variables were integrated to construct nomograms for 3- and 5-year survival. Calibration plots for the 3- and 5-year survival in training and validation sets showed that the prediction curve was close to a 45 degree slash. The C-indices of OS in training and validation cohorts were 0.705 and 0.678, respectively. Similar results were observed for CSS in training and validation cohorts.

Conclusions

Our proposed nomograms can effectively and accurately predict the prognosis of BC patients with bone metastasis at presentation, which provide a basis for individual treatments for metastatic lesions.

Tumor Size Improves the Accuracy of the Prognostic Prediction of Lymph Node-Negative Gastric Cancer

BACKGROUND

Tumor size has been regarded as the "T" stage of many solid tumors because of its effect on prognosis. However, the prognostic impact of tumor size in gastric cancer (GC) is still controversial.

MATERIALS AND METHODS

A total of 436 patients with curatively resected GC and those without lymph node metastasis in our center were retrospectively enrolled. The appropriate cutoff points for tumor size were determined. Potential prognostic factors were analyzed. In addition, a pathological tumor-size (pTS) classification system was proposed to evaluate the superiority of its prognostic prediction of node-negative GC patients compared with that of the pT staging system.

RESULTS

The ideal cutoff points for tumor size were 4 and 8 cm. In the multivariate analysis, tumor size was identified as an independent prognostic factor for node-negative GC patients after surgery, as was pT stage. The pTS classification was found to be more appropriate for predicting the overall survival of node-negative GC patients after curative surgery than pT stage, and the -2 log-likelihood of the pTS classification (1680.782) was smaller than the value of pT (1695.239).

CONCLUSIONS

As an independent prognostic factor, tumor size should be incorporated into the pT staging system to enhance the accuracy of the prognostic prediction of node-negative GC patients.

Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm

Breast cancer is the most common cancer among women and is considered a major public health concern worldwide. Biogeography-based optimization (BBO) is a novel metaheuristic algorithm. This study analyzed the relationship between the clinicopathologic variables of breast cancer using Cox proportional hazard (PH) regression on the basis of the BBO algorithm. The dataset is prospectively maintained by the Division of Breast Surgery at Kaohsiung Medical University Hospital. A total of 1896 patients with breast cancer were included and tracked from 2005 to 2017. Fifteen general breast cancer clinicopathologic variables were collected. We used the BBO algorithm to select the clinicopathologic variables that could potentially contribute to predicting breast cancer prognosis. Subsequently, Cox PH regression analysis was used to demonstrate the association between overall survival and the selected clinicopathologic variables. C-statistics were used to test predictive accuracy and the concordance of various survival models. The BBO-selected clinicopathologic variables model obtained the highest C-statistic value (80%) for predicting the overall survival of patients with breast cancer. The selected clinicopathologic variables included tumor size (hazard ratio [HR] 2.372, p = 0.006), lymph node metastasis (HR 1.301, p = 0.038), lymphovascular invasion (HR 1.606, p = 0.096), perineural invasion (HR 1.546, p = 0.168), dermal invasion (HR 1.548, p = 0.028), total mastectomy (HR 1.633, p = 0.092), without hormone therapy (HR 2.178, p = 0.003), and without chemotherapy (HR 1.234, p = 0.491). This number was the minimum number of discriminators required for optimal discrimination in the breast cancer overall survival model with acceptable prediction ability. Therefore, on the basis of the clinicopathologic variables, the survival prediction model in this study could contribute to breast cancer follow-up and management.

Oncological safety of autologous breast reconstruction after mastectomy for invasive breast cancer

Background

The number of patients requesting autologous breast reconstruction (ABR) after mastectomy for breast cancer has increased over the past decades. However, concern has been expressed about the oncological safety of ABR. The aim of our study was to assess the effect of ABR on distant relapse.

Methods

In this retrospective cohort study, data was analysed from patients who underwent mastectomy for invasive breast cancer in University Hospitals Leuven between 2000 and 2011. In total, 2326 consecutive patients were included, 485 who underwent mastectomy with ABR and 1841 who underwent mastectomy alone. The risk of relapse in both groups was calculated using a Cox proportional hazards analysis, adjusted for established prognostic factors. ABR was considered as a time-dependent variable. Additionally, the evolution of the risk over follow-up time was calculated.

Results

With a median follow-up of 68 months, 8% of patients in the reconstruction group developed distant metastases compared to 15% in the mastectomy alone group (univariate HR 0.70, 95% CI 0.50–0.97, p = 0.0323). However, after adjustment for potential confounding factors in a Cox multivariable analysis, the risk of distant relapse was no longer significantly different between groups (multivariate HR 0.82, 95% CI 0.55–1.22, p = 0.3301). Moreover, the risk of metastasis after reconstruction was not time-dependent.

Conclusions

These findings suggest that there is no effect of ABR on distant relapse rate and thus that ABR is an oncological safe procedure. The rate of local recurrence was too low to make any significant conclusions.

Personalisation of breast cancer follow-up: a time-dependent prognostic nomogram for the estimation of annual risk of locoregional recurrence in early breast cancer patients

The objective of this study was to develop and validate a time-dependent logistic regression model for prediction of locoregional recurrence (LRR) of breast cancer and a web-based nomogram for clinical decision support. Women first diagnosed with early breast cancer between 2003 and 2006 in all Dutch hospitals were selected from the Netherlands Cancer Registry (n = 37,230). In the first 5 years following primary breast cancer treatment, 950 (2.6 %) patients developed a LRR as first event. Risk factors were determined using logistic regression and the risks were calculated per year, conditional on not being diagnosed with recurrence in the previous year. Discrimination and calibration were assessed. Bootstrapping was used for internal validation. Data on primary tumours diagnosed between 2007 and 2008 in 43 Dutch hospitals were used for external validation of the performance of the nomogram (n = 12,308). The final model included the variables grade, size, multifocality, and nodal involvement of the primary tumour, and whether patients were treated with radio-, chemo- or hormone therapy. The index cohort showed an area under the ROC curve of 0.84, 0.77, 0.70, 0.73 and 0.62, respectively, per subsequent year after primary treatment. Model predictions were well calibrated. Estimates in the validation cohort did not differ significantly from the index cohort. The results were incorporated in a web-based nomogram (http://www.utwente.nl/mira/influence). This validated nomogram can be used as an instrument to identify patients with a low or high risk of LRR who might benefit from a less or more intensive follow-up after breast cancer and to aid clinical decision making for personalised follow-up.

Are two-centimeter breast cancers large or small?

BACKGROUND

Node-negative breast cancers from 2 cm to 5 cm in size are classified as stage ii, and smaller cancers, as stage i. We sought to determine if the prognosis of women with a breast cancer exactly 2 cm in size more closely resembles that of women with a stage i or a stage ii breast cancer.

METHODS

Using a cohort of 4265 young women with breast cancer, we compared the 10-year breast cancer mortality rates for women who had a tumour 0.1-1.9 cm, exactly 2.0 cm, and 2.1-2.9 cm.

RESULTS

In the first 3 years after diagnosis, the survival pattern of women with a 2.0-cm breast cancer was nearly identical to that of women with a larger cancer (2.1-3.0 cm). From year 3 to year 10, the relative survival of women with a 2.0-cm breast cancer was improved and nearly identical to that of women with a smaller cancer. The 10-year survival rate was 89.3% for women with tumours less than 20 mm, 86.1% for women with tumours equal to 20 mm, and 81.2% for women with 21-mm to 29-mm tumours.

CONCLUSIONS

For young women with small breast cancers, the relative mortality from breast cancer is dynamic with increasing tumour size and varies with time from diagnosis.