Comparison of the Real-World Reporting of Symptoms and Well-Being for the HER2-Directed Trastuzumab Biosimilar Ogivri With Registry Data for Herceptin in the Treatment of Breast Cancer: Prospective Observational Study (OGIPRO) of Electronic Patient-Reported Outcomes.

BACKGROUND: Trastuzumab has had a major impact on the treatment of human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). Anti-HER2 biosimilars such as Ogivri have demonstrated safety and clinical equivalence to trastuzumab (using Herceptin as the reference product) in clinical trials. To our knowledge, there has been no real-world report of the side effects and quality of life (QoL) in patients treated with biosimilars using electronic patient-reported outcomes (ePROs). OBJECTIVE: The primary objective of this prospective observational study (OGIPRO study) was to compare the ePRO data related to treatment side effects collected with the medidux app in patients with HER2-positive BC treated with the trastuzumab biosimilar Ogivri (prospective cohort) to those obtained from historical cohorts treated with Herceptin alone or combined with pertuzumab and/or chemotherapy (ClinicalTrials.gov NCT02004496 and NCT03578731). METHODS: Patients were treated with Ogivri alone or combined with pertuzumab and/or chemotherapy and hormone therapy in (neo)adjuvant and palliative settings. Patients used the medidux app to dynamically record symptoms (according to the Common Terminology Criteria for Adverse Events [CTCAE]), well-being (according to the Eastern Cooperative Oncology Group Performance Status scale), QoL (using the EQ-5D-5L questionnaire), cognitive capabilities, and vital parameters over 6 weeks. The primary endpoint was the mean CTCAE score. Key secondary endpoints included the mean well-being score. Data of this prospective cohort were compared with those of the historical cohorts (n=38 patients; median age 51, range 31-78 years). RESULTS: Overall, 53 female patients with a median age of 54 years (range 31-87 years) were enrolled in the OGIPRO study. The mean CTCAE score was analyzed in 50 patients with available data on symptoms, while the mean well-being score was evaluated in 52 patients with available data. The most common symptoms reported in both cohorts included fatigue, taste disorder, nausea, diarrhea, dry mucosa, joint discomfort, tingling, sleep disorder, headache, and appetite loss. Most patients experienced minimal (grade 0) or mild (grade 1) toxicities in both cohorts. The mean CTCAE score was comparable between the prospective and historical cohorts (29.0 and 30.3, respectively; mean difference -1.27, 95% CI -7.24 to 4.70; P=.68). Similarly, no significant difference was found for the mean well-being score between the groups treated with the trastuzumab biosimilar Ogivri and Herceptin (74.3 and 69.8, respectively; mean difference 4.45, 95% CI -3.53 to 12.44; P=.28). CONCLUSIONS: Treatment of patients with HER2-positive BC with the trastuzumab biosimilar Ogivri resulted in equivalent symptoms, adverse events, and well-being as found for patients treated with Herceptin as determined by ePRO data. Hence, integration of an ePRO system into research and clinical practice can provide reliable information when investigating the real-world tolerability and outcomes of similar therapeutic compounds. TRIAL REGISTRATION: ClinicalTrials.gov NCT05234021; https://clinicaltrials.gov/study/NCT05234021.

Towards an early warning system for monitoring of cancer patients using hybrid interactive machine learning.

Background: The use of smartphone apps in cancer patients undergoing systemic treatment can promote the early detection of symptoms and therapy side effects and may be supported by machine learning (ML) for timely adaptation of therapies and reduction of adverse events and unplanned admissions. Objective: We aimed to create an Early Warning System (EWS) to predict situations where supportive interventions become necessary to prevent unplanned visits. For this, dynamically collected standardized electronic patient reported outcome (ePRO) data were analyzed in context with the patient's individual journey. Information on well-being, vital parameters, medication, and free text were also considered for establishing a hybrid ML model. The goal was to integrate both the strengths of ML in sifting through large amounts of data and the long-standing experience of human experts. Given the limitations of highly imbalanced datasets (where only very few adverse events are present) and the limitations of humans in overseeing all possible cause of such events, we hypothesize that it should be possible to combine both in order to partially overcome these limitations. Methods: The prediction of unplanned visits was achieved by employing a white-box ML algorithm (i.e., rule learner), which learned rules from patient data (i.e., ePROs, vital parameters, free text) that were captured via a medical device smartphone app. Those rules indicated situations where patients experienced unplanned visits and, hence, were captured as alert triggers in the EWS. Each rule was evaluated based on a cost matrix, where false negatives (FNs) have higher costs than false positives (FPs, i.e., false alarms). Rules were then ranked according to the costs and priority was given to the least expensive ones. Finally, the rules with higher priority were reviewed by two oncological experts for plausibility check and for extending them with additional conditions. This hybrid approach comprised the application of a sensitive ML algorithm producing several potentially unreliable, but fully human-interpretable and -modifiable rules, which could then be adjusted by human experts. Results: From a cohort of 214 patients and more than 16'000 available data entries, the machine-learned rule set achieved a recall of 19% on the entire dataset and a precision of 5%. We compared this performance to a set of conditions that a human expert had defined to predict adverse events. This "human baseline" did not discover any of the adverse events recorded in our dataset, i.e., it came with a recall and precision of 0%. Despite more plentiful results were expected by our machine learning approach, the involved medical experts a) had understood and were able to make sense of the rules and b) felt capable to suggest modification to the rules, some of which could potentially increase their precision. Suggested modifications of rules included e.g., adding or tightening certain conditions to make them less sensitive or changing the rule consequences: sometimes further monitoring the situation, applying certain test (such as a CRP test) or applying some simple pain-relieving measures was deemed sufficient, making a costly consultation with the physician unnecessary. We can thus conclude that it is possible to apply machine learning as an inspirational tool that can help human experts to formulate rules for an EWS. While humans seem to lack the ability to define such rules without such support, they are capable of modifying the rules to increase their precision and generalizability. Conclusions: Learning rules from dynamic ePRO datasets may be used to assist human experts in establishing an early warning system for cancer patients in outpatient settings.

Does guideline-adherent therapy improve the outcome for early-onset breast cancer patients?

BACKGROUND AND OBJECTIVE: Guidelines for the treatment of early-onset breast cancer have been proposed in several countries, but to date, their impact on outcomes is unverified. The objective of this study was to evaluate the association between guideline-adherent versus nonadherent treatment and recurrence-free survival (RFS) and overall survival (OAS) in early-onset breast cancer patients. METHODS: A total of 1,778 patients were included in the study, of whom 111 were 35 years or younger and 1,667 were between 36 and 55 years. RFS and OAS were compared between the two groups, with respect to multiple parameters. All survival data were adjusted for tumor characteristics and analyzed with respect to guideline adherence according to the German Step 3 guidelines. RESULTS: Statistically significant differences between the two groups (<35 years, 36-55 years) were observed with regard to breast surgery (p = 0.002) and hormone therapy (p = 0.006). Both groups were treated identically in terms of guideline adherence concerning axillary dissection (p = 0.9), radiation therapy (p = 0.7) and chemotherapy (p = 0.556). Young breast cancer patients whose treatment adhered to guideline recommendations had increased RFS and OAS [RFS: p = 0.030, hazard ratio (HR) 2.95, 95% confidence interval (CI) 1.11-7.83; OAS: p < or = 0.001, HR 2.92, 95% CI 2.01-4.23]. CONCLUSION: Guideline-adherent treatment for early-onset breast cancer patients significantly improves OAS and RFS and should therefore be demanded for all patients.

Impact of guideline conformity on breast cancer therapy: results of a 13-year retrospective cohort study.

BACKGROUND: To date, few studies have investigated whether the implementation of national breast cancer guidelines fulfills the goal to optimize the national standard of care. Therefore, we aimed to evaluate retrospectively the guideline-related 13-year data on breast cancer patients treated at our institution. PATIENTS AND METHODS: In a retrospective cohort study, the records of a total of 2,231 patients with primary breast cancer treated during the period of 1992-2005 at the Department of Obstetrics and Gynecology, University of Ulm, Germany, were analyzed. Based on the German national Step 3 (S3) guideline, a model was created to classify groups according to therapy 'conforming' and 'non-conforming' to guideline recommendations. RESULTS: In 2005, 70.2% of all patients included received both surgical and systemic adjuvant therapies conforming to the guideline. Guideline-conforming treatment was accompanied with significant advantages in terms of recurrence-free survival (RFS) and overall survival (OAS) rates. CONCLUSIONS: It has to be demanded that breast cancer patients are treated in conformity with the S3 guidelines. The reasons for a treatment not conforming to the guidelines should be analyzed for the detection of barrier factors, in order to optimize adherence to the guidelines and therefore to prolong RFS and OAS.

Comparison of early onset breast cancer patients to older premenopausal breast cancer patients.

BACKGROUND: The objective of this study was to show differences between breast cancer patients < or =35 and >35 years with regard to tumor characteristics and to present the patient-relevant outcomes overall survival (OAS) and recurrence-free survival (RFS). METHODS: We analyzed data from 119 women aged 35 years or younger with breast cancer and compared multiple parameters against breast cancer patients between 36 and 55 (n = 1,097), all pre-menopausal. Data were adjusted for tumor characteristics and therapy. RESULTS: There was no statistically significant difference in tumor size, axillary lymph node involvement, and histological subtypes. On the contrary, grading lymphovascular invasion and receptor negativity showed statistically significant differences. Unadjusted hazard ratio are 2.11 (1.32-3.39) (OAS) and 1.92 (1.35-2.73) (RFS). Multi-adjusted hazard ratio are 2.97 (1.70-5.18) (OAS) and 2.11 (1.42-3.13) (RFS). CONCLUSIONS: In conclusion, young breast cancer patients still have a poor prognosis. Even after adjustment of the data, OAS and RFS showed a worse prognosis. Normal prognostic factors like tumor size, axillary lymph node involvement, and grading can therefore be not the explanation for the more aggressive disease progress within early onset breast cancer patients.

[Integrating the e-learning programme EGONE into the block of training in obstetrics and gynaecology]. / Integration des E-Learning-Programmes EGONE in das Blockpraktikum der Gynäkologie/Geburtshilfe.

OBJECTIVE: EGONE is an E-Learning Forum for Gynaecology, Obstetrics, Neonatology and Reproductive Endocrinology based on the Swiss Catalogue of Learning Objectives. For two semesters, students attending the gynaecology block at the Medical Faculty of the University of Ulm have been provided with licences to use EGONE. Students can work on a specially equipped computer and practise whenever they want. The aim of this study was to generate hypotheses as to which factors favour the use of EGONE and which didactic implications for the learning success the application of EGONE has. METHODS: During August 2009, 28 medical students in their 8th and 9th semester were interviewed after having completed their block of training in gynaecology. The instruments used included a questionnaire and a partially standardised interview. RESULTS: We found that the e-learning offering EGONE was basically met with a positive response from the medical students at the University of Ulm. Regarding the integration of EGONE, three problem areas were identified: shortage of equipment, lack of dependable access and functional, but not curricular integration. Students' suggestions for better integration of EGONE were related to two subject areas: establishing an assisted learning centre (e.g., PC pool with library) and developing curricular independence and relevance (e.g., specific application to patient cases, conducting seminars with EGONE). CONCLUSION: The integration of the e-learning programme EGONE presupposes a logical, didactic concept for the whole clinical block of training in gynaecology as well as dependable, sufficient infrastructure and technical equipment and providing didactic support to users.

Haemorrhage and nerve damage as complications of TVT-O procedure: case report and literature review.

The transobturatorial vaginal tape procedure is associated with little complication rate. Bladder perforation, urethral invasion, vaginal erosion, postoperative bladder retention, de novo incontinence and retropubic pain and haematoma are the most reported complications. The aim of this article is to present an uncommon complication in a patient operated by transobturator vaginal tape with an inside-outside route.