The impact of hospital type on the efficacy of chemotherapy treatment in ovarian cancer patients

Association between hospital volume and outcomes in invasive ovarian cancer in Belgium: A population-based study

OBJECTIVES

To study the association between hospital volume and outcomes in patients with invasive epithelial ovarian cancer (EOC).

METHODS

This study included 3988 patients diagnosed with invasive EOC between 2014 and 2018, selected from the population-based database of the Belgian Cancer Registry (BCR), and coupled with health insurance and vital status data. The associations between hospital volume and observed survival since diagnosis were assessed with Cox proportional hazard models, while volume associations with 30-day post-operative mortality and complicated recovery were evaluated using logistic regression models.

RESULTS

Treatment for EOC was very dispersed with half of the 100 centres treating fewer than six patients per year. The median survival of patients treated in centres with the highest-volume quartile was 2.5 years longer than in those with the lowest-volume quartile (4.2 years versus 1.7 years). When taking the case-mix of hospitals into account, patients treated in the lowest volume centres had a 47% higher hazard to die than patients treated in the highest volume centres (HR: 1.47, 95% CI: 1.11-1.93, p = 0.006) over the first five years after incidence. A similar association was found when focussing on the surgical volume of the hospitals and considering only operated patients with invasive EOC. Lastly, the 30-day post-operative mortality decreased significantly with increasing surgical volume.

CONCLUSIONS

The large dispersion of care and expertise within Belgium and the volume-outcome associations observed in this study support the implementation of the concentration of care for patients with invasive EOC in reference centres.

Malignancy Assessment Using Gene Identification in Captured Cells Algorithm for the Prediction of Malignancy in Women With a Pelvic Mass

OBJECTIVE

To evaluate the detection of malignancy in women with a pelvic mass by using multiplexed gene expression analysis of cells captured from peripheral blood.

METHODS

This was an IRB-approved, prospective clinical study. Eligible patients had a pelvic mass and were scheduled for surgery or biopsy. Rare cells were captured from peripheral blood obtained preoperatively by using a microfluidic cell capture device. Isolated mRNA from the captured cells was analyzed for expression of 72 different gene transcripts. Serum levels for several commonly assayed biomarkers were measured. All patients had a tissue diagnosis. Univariate and multivariate logistic regression analyses for the prediction of malignancy using gene expression and serum biomarker levels were performed, and receiver operating characteristic curves were constructed and compared.

RESULTS

A total of 183 evaluable patients were enrolled (average age 56 years, range 19-91 years). There were 104 benign tumors, 17 low malignant potential tumors, and 62 malignant tumors. Comparison of the area under the receiver operating characteristic curve for individual genes and various combinations of genes with or without serum biomarkers to differentiate between benign conditions (excluding low malignant potential tumors) and malignant tumors showed that a multivariate model combining the expression levels of eight genes and four serum biomarkers achieved the highest area under the curve (AUC) (95.1%, 95% CI 92.0-98.2%). The MAGIC (Malignancy Assessment using Gene Identification in Captured Cells) algorithm significantly outperformed all individual genes (AUC 50.2-65.2%; all P <.001) and a multivariate model combining 14 different genes (AUC 88.0%, 95% CI 82.9-93.0%; P =.005). Further, the MAGIC algorithm achieved an AUC of 89.5% (95% CI 81.3-97.8%) for stage I-II and 98.9% (95% CI 96.7-100%) for stage III-IV patients with epithelial ovarian cancer.

CONCLUSION

Multiplexed gene expression evaluation of cells captured from blood, with or without serum biomarker levels, accurately detects malignancy in women with a pelvic mass.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT02781272.

FUNDING SOURCE

This study was funded by ANGLE Europe Limited (Surrey Research Park, Guildford, Surrey, United Kingdom).

Do hospital type or caseload make a difference in chemotherapy treatment patterns for early breast cancer? Results from 104 German institutions, 2008-2017

BACKGROUND

Over the past decade, chemotherapy has been used more selectively in early breast cancer (EBC) due to better risk stratification. Neoadjuvant chemotherapy (NACT) has evolved to the primary treatment option. The type and size of hospitals is known to have a substantial influence on the kinds of treatment they provide, and therefore on patient outcomes (e.g. rates for pathological complete response, pCR), but it is not yet known how this has affected delivery of chemotherapy for EBC in Germany.

METHODS

This study analyzed chemotherapy use and pCR rates after NACT for EBC patients treated at 104 German institutions 2008-2017. Institutions were separated into associated hospital type (university hospital; teaching hospital; community hospital) and annual caseload (≤100; 101-250; >250 cases/year).

RESULTS

Overall, 124,084 patients were included, of whom 11.6% were treated at university hospitals, 63.1% at teaching hospitals, and 25.3% at community hospitals. In total, 46,274 (37.3%) received chemotherapy, of whom 44,765 had information available about systemic treatment and surgery. From 2008 to 2017, chemotherapy use declined from 48.3% to 36.4% for university hospitals, from 40.7% to 30.3% for teaching hospitals, and from 42.4% to 33.7% for community hospitals. Furthermore, the proportion of NACT increased the most in university hospitals (from 32.0% to 68.1%); whereas, the rate of pCR (defined as ypT0 ypN0) increased irrespective of institutional type. Analyses regarding annual caseload did not show any differences.

CONCLUSIONS

The results from this large, nationwide cohort reflect a more selective use of chemotherapy in Germany, irrespective of institutional type or case load.

The optimal organization of gynecologic oncology services: a systematic review

BACKGROUND

A system-level organizational guideline for gynecologic oncology was identified by a provincial cancer agency as a key priority based on input from stakeholders, data showing more limited availability of multidisciplinary or specialist care in lower-volume than in higher-volume hospitals in the relevant jurisdiction, and variable rates of staging for ovarian and endometrial cancer patients.

METHODS

A systematic review assessed the relationship of the organization of gynecologic oncology services with patient survival and surgical outcomes. The electronic databases medline and embase (ovid: 1996 through 9 January 2015) were searched using terms related to gynecologic malignancies combined with organization of services, patterns of care, and various facility and physician characteristics. Outcomes of interest included overall or disease-specific survival, short-term survival, adequate staging, and degree of cytoreduction or optimal cytoreduction (or both) for ovarian cancer patients by hospital or physician type, and rate of discrepancy in initial diagnoses and intraoperative consultation between non-specialist pathologists and gyne-oncology-specialist pathologists.

RESULTS

One systematic review and sixteen additional primary studies met the inclusion criteria. The evidence base as a whole was judged to be of lower quality; however, a trend toward improved outcomes with centralization of gynecologic oncology was found, particularly with respect to the gynecologic oncology care of patients with advanced-stage ovarian cancer.

CONCLUSIONS

Improvements in outcomes with centralization of gynecologic oncology services can be attributed to a number of factors, including access to specialist care and multidisciplinary team management. Findings of this systematic review should be used with caution because of the limitations of the evidence base; however, an expert consensus process made it possible to create recommendations for implementation.