Digitally Enabled Transitional Care Management in Oncology

PURPOSE

Improving care transitions for patients with cancer discharged from the hospital is considered an important component of quality care. Digital monitoring has the potential to better the delivery of transitional care through improved patient-provider communication and enhanced symptom management. However, remote patient monitoring (RPM) interventions have not been widely implemented for oncology patients after discharge, an innovative setting in which to apply this technology.

METHODS

We implemented a RPM intervention which identifies medical oncology patients at discharge, monitors their symptoms for 10 days, and intervenes as necessary to manage symptoms. We evaluated the feasibility (>50% patient engagement with symptom assessment), appropriateness (symptom alerts), and acceptability (net promoter score >0.7) of the intervention and the initial effect on acute care visits and return on investment.

RESULTS

During the study period, January 1, 2021, to December 31, 2022, we evaluated 2,257 medical oncology discharges representing 1,857 unique patients. We found that 65.9% of patients discharged (N = 1,489) completed at least one symptom assessment postdischarge and of them, 45.5% (n = 678) generated a severe symptom alert that we helped to manage. Patients expressed high satisfaction with the intervention with a net promoter score of 84%. In preliminary analysis of patients with GI malignancies (n = 449), we found a nonsignificant decrease in 30-day readmissions for the intervention cohort (n = 269) by 5.8% as compared with the control (n = 180; from 33.3% to 27.5%; P = .22).

CONCLUSION

Digital transitional care management was feasible and demonstrated that patients transitioning from the hospital to home have a substantial symptom burden. The intervention was associated with high patient satisfaction but will require further refinement and evaluation to increase its impact on 30-day readmission.

Association Between Remote Monitoring and Acute Care Visits in High-Risk Patients Initiating Intravenous Antineoplastic Therapy

PURPOSE

Traditional oncology care models have not effectively identified and managed at-risk patients to prevent acute care. A next step is to harness advances in technology to enable patients to report symptoms any time, enabling digital hovering-intensive symptom monitoring and management. Our objective was to evaluate a digital platform that identifies and remotely monitors high-risk patients initiating antineoplastic therapy with the goal of preventing acute care visits.

METHODS

This was a single-institution matched cohort quality improvement study conducted at a National Cancer Institute-designated cancer center between January 1, 2019, and March 31, 2020. Eligible patients were those initiating intravenous antineoplastic therapy who were identified as high risk for seeking acute care. Enrolled patients' symptoms were monitored using a digital platform. A dedicated team of clinicians managed reported symptoms. The primary outcomes of emergency department visits and hospitalizations within 6 months of treatment initiation were analyzed using cumulative incidence analyses with a competing risk of death.

RESULTS

Eighty-one patients from the intervention arm were matched by stage and disease with contemporaneous high-risk control patients. The matched cohort had similar baseline characteristics. The cumulative incidence of an emergency department visit for the intervention cohort was 0.27 (95% CI, 0.17 to 0.37) at six months compared with 0.47 (95% CI, 0.36 to 0.58) in the control (P = .01) and of an inpatient admission was 0.23 (95% CI, 0.14 to 0.33) in the intervention cohort versus 0.41 (95% CI, 0.30 to 0.51) in the control (P = .02).

CONCLUSION

The narrow employment of technology solutions to complex care delivery challenges in oncology can improve outcomes and innovate care. This program was a first step in using a digital platform and a remote team to improve symptom care for high-risk patients.

Remote symptom monitoring after hospital discharge

1517

Background: Strategies to improve transitions from the hospital to home for patients with cancer are considered an important component of quality, patient-centered care in oncology. CMS evaluates cancer hospital performance based on the 30-day unplanned hospital readmission rate, and this measure has been endorsed by the National Quality Forum. Nationally, the 30-day readmission rate for oncology patients ranges from 19%-27%. These readmissions come at high psychosocial, physical, and financial costs for patients and caregivers. A remote monitoring intervention that includes frequent contacts with the patient is likely to be effective in improving this transition. Methods: We evaluated the feasibility, acceptability, and perceived value of a mobile health intervention to monitor and manage symptoms of adult medical and surgical oncology patients discharged from an NCI-designated cancer center to home. Patients were monitored for 10 days, which is the median time to readmission for an oncology patient. The technology supporting the program included: 1) a patient portal enabling daily electronic patient-reported outcomes assessments; 2) a pulse oximeter to provide data on blood oxygen level and heart rate; 3) alerts for concerning symptoms; 4) an application to allow staff to review and trend symptom data; 5) a secure platform to support communications and televisits between staff and patients; 6) an advanced feedback report to provide just-in-time patient symptom education. Feasibility and acceptability were evaluated through engagement (goal: > 50% response rate) and symptom alerts and perceived value was measured through a patient engagement survey that included a net promoter score (how likely the patient is to recommend the program to similar patients; goal > 0.7). Results: Between September 27, 2020 to December 31, 2021, the program enrolled 1,091 medical oncology (median age: 63 years, 55% female) and 4,222 surgical oncology patients (median age: 63 years,55% female). Of those enrolled, 65% of medical and 74% of surgical oncology patients participated in home remote monitoring by self-reporting symptom data. This resulted in 2,869 completed symptom assessment from medical and 16,009 completed assessments from surgical patients. Sixty-three percent of medical oncology assessments resulted in a yellow (moderate) or red (severe) symptom alert compared with 26% for surgical oncology patients. Pain was the predominant symptom generating red alerts for medical oncology patients (17%). Fifty-two percent of patients completed the engagement survey, and the net promoter score was 0.82. Conclusions: A remote monitoring program after discharge was feasible, acceptable, and perceived to be of value by oncology patients discharged from a cancer center. Surgical and medical patients have similar response rates but differ in symptom burden. Future work will evaluate the value of a remote symptom monitoring platform in decreasing readmissions.

Association between remote monitoring and acute care visits in high-risk patients initiating intravenous antineoplastic therapy

1578

Background: Acute care visits (emergency department [ED] visits or inpatient admissions) for patients with cancer are growing disproportionately. Traditional oncology care models have not effectively identified and managed at-risk patients to prevent acute care. A next step is to harness advances in technology and mobile applications to enable patients to report symptoms any time, enabling “digital hovering” - intensive monitoring and management of high-risk patients. Our objective was to evaluate a digital platform that identifies and remotely monitors high-risk patients initiating intravenous antineoplastic therapy with the goal of preventing unnecessary acute care visits. Methods: This was a single-institution matched cohort quality improvement study conducted at an NCI-designated cancer center between January 1, 2019 and March 31, 2020. Eligible patients were those initiating intravenous antineoplastic therapy who were identified as high-risk for seeking acute care. Patients were identified as high-risk for an acute care visit by their oncologist with decision support from a web-based machine learning model. Enrolled patients’ symptoms were monitored using a digital platform. The platform is integrated into the EMR and includes: 1) a secure patient portal enabling communication and daily delivery of electronic patient-reported outcomes symptom assessments; 2) clinical alerts for concerning symptoms; and 3) a symptom trending application. A dedicated team of registered nurses and nurse practitioners managed reported symptoms. These clinicians acted as an extension of the primary oncology team, assisting with patient management exclusively through the platform. The primary outcomes evaluated were incidence of ED visits and inpatient admissions within six months of intravenous antineoplastic initiation. Results: Eighty-one high-risk patients from the intervention arm were matched by stage and disease with contemporaneous high-risk control patients. Matched cohorts had similar baseline characteristics, including age, sex, race, and treatment. ED visits and hospitalizations within six months of treatment initiation were analyzed using cumulative incidence analyses with a competing risk of death. The cumulative incidence of an ED visit for the intervention cohort was 0.27 (95% CI: 0.17, 0.37) at six months compared to 0.47 (95% CI: 0.36, 0.58) in the control group (p = 0.01). The cumulative incidence of an inpatient admission was 0.23 (95% CI: 0.14, 0.33) in the intervention group versus 0.41 (95% CI: 0.30, 0.51) in the control group (p = 0.02). Conclusions: The narrow employment of technology solutions to complex care delivery challenges in oncology can improve outcomes and innovate care. This program was a first step in using a digital platform and a remote team to improve symptom care in the home for high-risk patients.

Analysis of a Remote Monitoring Program for Symptoms Among Adults With Cancer Receiving Antineoplastic Therapy

IMPORTANCE

Electronic patient-reported outcomes (ePROs) may have the potential to improve cancer care delivery by enhancing patient quality of life, reducing acute care visits, and extending overall survival. However, the optimal cadence of ePRO assessments is unknown.

OBJECTIVE

To determine patient response preferences and the clinical value associated with a daily cadence for ePROs for patients receiving antineoplastic treatment.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement study of adult patients undergoing antineoplastic treatment assessed a remote monitoring program using ePROs that was developed to manage cancer therapy-related symptoms. ePRO data submitted between October 16, 2018 to February 29, 2020, from a single regional site within the Memorial Sloan Kettering Cancer Center network were included. Data were analyzed from April 2020 to January 2022.

EXPOSURE

While undergoing active treatment, patients received a daily ePRO assessment that, based on patient responses, generated yellow (moderate) or red (severe) symptom alerts that were sent to clinicians.

MAIN OUTCOMES AND MEASURES

The main outcomes assessed included patient response rate, symptom alert frequency, and an analysis of the clinical value of daily ePROs.

RESULTS

A total of 217 patients (median [range] age, 66 [31-92] years; 103 [47.5%] women and 114 [52.5%] men) initiating antineoplastic therapy at high risk for symptoms were monitored for a median (range) of 91 (2-369) days. Most patients had thoracic (59 patients [27.2%]), head and neck (48 patients [22.1%]), or gastrointestinal (43 patients [19.8%]) malignant neoplasms. Of 14 603 unique symptom assessments completed, 7349 (50.3%) generated red or yellow symptom alerts. Symptoms commonly generating alerts included pain (665 assessments [23.0%]) and functional status (465 assessments [16.1%]). Most assessments (8438 assessments [57.8%]) were completed at home during regular clinic hours (ie, 9 am-5 pm), with higher response rates on weekdays (58.4%; 95% CI, 57.5%-59.5%) than on weekend days (51.3%; 95% CI, 49.5%-53.1%). Importantly, 284 of 630 unique red alerts (45.1%) surfaced without a prior yellow alert for the same symptom within the prior 7 days; symptom severity fluctuated over the course of a week, and symptom assessments generating a red alert were followed by an acute care visit within 7 days 8.7% of the time compared with 2.9% for assessments without a red alert.

CONCLUSIONS AND RELEVANCE

These findings suggest that daily ePRO assessments were associated with increased insight into symptom management in patients undergoing antineoplastic treatment and symptom alerts were associated with risk of acute care.

Oncology Patients' Perspectives on Remote Patient Monitoring for COVID-19

PURPOSE

Oncology patients are vulnerable to adverse outcomes associated with COVID-19, and clinical deterioration must be identified early. Several institutions launched remote patient monitoring programs (RPMPs) to care for patients with COVID-19. We describe patients' perspectives on a COVID-19 RPMP at a National Comprehensive Cancer Center.

METHODS

Patients who tested positive for COVID-19 were eligible. Enrolled patients received a daily electronic COVID-19 symptom assessment, and a subset of high-risk patients also received a pulse oximeter. Monitoring was provided by a centralized team and was discontinued 14 days after a patient's positive test result and following 3 days without worsening symptoms. Patients who completed at least one assessment and exited the program were sent a patient engagement survey to evaluate the patient's experience with digital monitoring for COVID-19.

RESULTS

The survey was distributed to 491 patients, and 257 responded (52% completion rate). The net promoter score was 85%. Most patients agreed that the RPMP was worthwhile, enabled better management of their COVID-19 symptoms, made them feel more connected to their healthcare team, and helped prevent emergency room visits. Identified themes regarding patient-perceived value of a RPMP included (1) security: a clinical safety net; (2) connection: a link to their clinical team during a period of isolation; and (3) empowerment: an education on the virus and symptom management.

CONCLUSION

RPMPs are perceived to be of value to oncology patients with COVID-19. Policymakers should consider how these programs can be reimbursed to keep vulnerable patients at home and out of the acute care setting.

Building a Clinically Relevant Risk Model: Predicting Risk of a Potentially Preventable Acute Care Visit for Patients Starting Antineoplastic Treatment

PURPOSE

To create a risk prediction model that identifies patients at high risk for a potentially preventable acute care visit (PPACV).

PATIENTS AND METHODS

We developed a risk model that used electronic medical record data from initial visit to first antineoplastic administration for new patients at Memorial Sloan Kettering Cancer Center from January 2014 to September 2018. The final time-weighted least absolute shrinkage and selection operator model was chosen on the basis of clinical and statistical significance. The model was refined to predict risk on the basis of 270 clinically relevant data features spanning sociodemographics, malignancy and treatment characteristics, laboratory results, medical and social history, medications, and prior acute care encounters. The binary dependent variable was occurrence of a PPACV within the first 6 months of treatment. There were 8,067 observations for new-start antineoplastic therapy in our training set, 1,211 in the validation set, and 1,294 in the testing set.

RESULTS

A total of 3,727 patients experienced a PPACV within 6 months of treatment start. Specific features that determined risk were surfaced in a web application, riskExplorer, to enable clinician review of patient-specific risk. The positive predictive value of a PPACV among patients in the top quartile of model risk was 42%. This quartile accounted for 35% of patients with PPACVs and 51% of potentially preventable inpatient bed days. The model C-statistic was 0.65.

CONCLUSION

Our clinically relevant model identified the patients responsible for 35% of PPACVs and more than half of the inpatient beds used by the cohort. Additional research is needed to determine whether targeting these high-risk patients with symptom management interventions could improve care delivery by reducing PPACVs.

InSight Care Pilot Program: Redefining Seeing a Patient

PURPOSE

Early detection and management of symptoms in patients with cancer improves outcomes. However, the optimal approach to symptom monitoring and management is unknown. InSight Care is a mobile health intervention that captures symptom data and facilitates patient-provider communication to mitigate symptom escalation.

PATIENTS AND METHODS

Patients initiating antineoplastic treatment at a Memorial Sloan Kettering regional location were eligible. Technology supporting the program included the following: a predictive model that identified patient risk for a potentially preventable acute care visit; a secure patient portal enabling communication, televisits, and daily delivery of patient symptom assessments; alerts for concerning symptoms; and a symptom-trending application. The main outcomes of the pilot were feasibility and acceptability evaluated through enrollment and response rates and symptom alerts, and perceived value evaluated on the basis of qualitative patient and provider interviews.

RESULTS

The pilot program enrolled 100 high-risk patients with solid tumors and lymphoma (29% of new treatment starts v goal of 25%). Over 6 months of follow-up, the daily symptom assessment response rate was 56% (the goal was 50%), and 93% of patients generated a severe symptom alert. Patients and providers perceived value in the program, and archetypes were developed for program improvement. Enrolled patients were less likely to use acute care than were other high-risk patients.

CONCLUSION

InSight Care was feasible and holds the potential to improve patient care and decrease facility-based care. Future work should focus on optimizing the cadence of patient assessments, the workforce supporting remote symptom management, and the return of symptom data to patients and clinical teams.

Implementation of Symptom Care Clinic (SCC) for acute symptoms management at outpatient oncology ambulatory centers

2030

Background: With improved overall cancer survival, increasing number of cancer patients are undergoing active treatment. This, in return, add burden in acute symptom management related to disease and treatment. This has resulted in increasing unplanned emergency room (ER) visits and negatively impacted patients experience and health cost. We establish Symptom Care Clinic (SCC) embedded in suburban ambulatory oncology centers to reduce unplanned ER lists and to improve patient experience. Methods: Together with all stakeholders, we developed six SCCs at regional ambulatory centers in NY and NJ. Clearly defined work flow and algorithm were developed to ensure appropriate patient referral. On-site radiology and laboratory services are available. The SCCs are staffed with combination of Advanced Practice Provided (APP) and physicians or APP alone supported by on site medical oncologist or remote central Urgent Care Center Attendings. We evaluated clinic volumes, reduction ins unplanned ER visits and patient experience. Results: From October 2017 to December 2019, total of 17,542 SCC visits were documented. Total of 17,479 lab and 5,355 radiology tests as well as 3,915 infusions were performed. The top five most common laboratory tests are CBC, blood cultures, CMP, respiratory panel and urine culture. The most common symptoms are fever, nausea/vomiting/dehydration, rash and pain. Among all SCC visits during this period, 83% were discharged home and 17% were transferred to ER or hospitals. During 2019, total 10,736 SCC visits were recored, APP evaluated 73.7% of visits and physicians 16.3% with comaprable recidivism rate, 2.52% and 2.75%, respectively. Conservatively, we estimated that approximately 40% of visits would have been Er visits based on numbers of CBC and other testes performed. Qualitative feedbacks from patients indicated positive experience in convenient access, cohesive care coordination and time saving from traveling to and waiting in ER. Conclusions: We successfully implemented an effective acute symptom management system in busy ambulatory oncology centers that is patient centric. Out data showed that SCC reduced unplanned ER visits and that APP/physician model has low recidivism rate.

Pilot program of remote monitoring for high-risk patients on antineoplastic treatment

2027

Background: Early detection and management of symptoms in patients with cancer improves outcomes, however, the optimal approach to symptom monitoring and management is unknown. This pilot program uses a mobile health intervention to capture and make accessible symptom data for high-risk patients to mitigate symptom escalation. Methods: Patients initiating antineoplastic treatment at a Memorial Sloan Kettering regional location were eligible. A dedicated staff of RNs and nurse practitioners managed the patients remotely. The technology supporting the program included: 1) a predictive model that identified patients at high risk for a potentially preventable acute care visit; 2) a patient portal enabling daily ecological momentary assessments (EMA); 3) alerts for concerning symptoms; 4) an application that allowed staff to review and trend symptom data; and 5) a secure messaging platform to support communications and televisits between staff and patients. Feasibility and acceptability were evaluated through enrollment (goal ≥25% of new treatment starts) and response rates (completion of > 50% of daily symptom assessments); symptom alerts; perceived value based on qualitative interviews with patients and providers; and acute care usage. Results: Between October 15, 2018 and July 10, 2019, the pilot enrolled 100 high-risk patients with solid tumors and lymphoma initiating antineoplastic treatment (median age: 66 years, 45% female). This represented 29% of patients starting antineoplastics. Over six months of follow-up, the response rate to the daily assessments was 56% and 93% of patients generated a severe symptom alert (Table). Both patients and providers perceived value in the program and 5,010 symptom-related secure messages were shared between staff and enrolled patients during the follow-up period. There was a preliminary signal in acute care usage with a 17% decrease in ED visits compared to a cohort of high-risk unenrolled patients. Conclusions: This pilot program of intensive monitoring of high-risk patients is feasible and holds significant potential to improve patient care and decrease hospital resources. Future work should focus on the optimal cadence of EMAs, the workforce to support remote symptom management, and how best to return symptom data to patients and clinical teams. [Table: see text]

A framework for building a clinically relevant risk model

6554

Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for emergency department (ED) visits enables institutions to target resources to those most likely to benefit. Risk stratification models developed to date have not been meaningfully employed in oncology, and there is a need for clinically relevant models to improve patient care. Methods: We established and applied a predictive framework for clinical use with attention to modeling technique, clinician feedback, and application metrics. The model employs electronic health record data from initial visit to first antineoplastic administration for patients at our institution from January 2014 to June 2017. The binary dependent variable is occurrence of an ED visit within the first 6 months of treatment. The final regularized multivariable logistic regression model was chosen based on clinical and statistical significance. In order to accommodate for the needs to the program, parameter selection and model calibration were optimized to suit the positive predictive value of the top 25% of observations as ranked by model-determined risk. Results: There are 5,752 antineoplastic administration starts in our training set, and 1,457 in our test set. The positive predictive value of this model for the top 25% riskiest new start antineoplastic patients is 0.53. From over 1,400 data features, the model was refined to include 400 clinically relevant ones spanning demographics, pathology, clinician notes, labs, medications, and psychosocial information. At the patient level, specific features determining risk are surfaced in a web application, RiskExplorer, to enable clinician review of individual patient risk. This physician facing application provides the individual risk score for the patient as well as their quartile of risk when compared to the population of new start antineoplastic patients. For the top quartile of patients, the risk for an ED visit within the first 6 months of treatment is greater than or equal to 49%. Conclusions: We have constructed a framework to build a clinically relevant risk model. We are now piloting it to identify those likely to benefit from a home-based, digital symptom management intervention.

Risk stratification and daily symptom monitoring for oncology patients

6535

Background: Monitoring and managing patient reported outcomes (PROs) has been recommended for oncology patients on active treatment but can be time and resource intensive. Identifying patients likely to benefit and the optimal frequency of PRO capture is still under investigation. We tested the feasibility of monitoring patients who are high-risk risk for acute care with daily PROs. Methods: Using data from our institution, we developed a model that employs over 400 clinical variables to calculate a patient’s risk of an emergency room visit within 6 months following the onset of treatment. From October 15, 2018 to January 23, 2019, we enrolled patients identified as high risk through a technology-enabled program to monitor and manage those patients’ symptoms. Enrolled patients entered PRO assessments daily via an online portal. Symptoms were monitored and managed by a centralized clinical team. Tiered notifications informed the team of concerning or escalating symptoms. We assessed how frequently patients completed symptom assessments and the frequency of symptom notifications. Results: During the pilot, 28 patients were identified as high risk and enrolled in the program (median age 65; 64% percent female). Disease types were: 15 (54%) thoracic, 7 (25%) gynecologic, 6 (21%) gastrointestinal. Median time in the program was 50 (6-98) days. Patients completed 840 of 1,350 assessments (62%). There were 328 assessments that triggered moderate alerts (39%) and 220 that triggered severe alerts (26%). The table describes the prevalence of symptoms at the patient-level. Conclusions: A model can be employed to identify high-risk patients in collaboration with clinicians. Our adherence rate with a daily symptom assessment was similar to those found in studies of less frequent PRO capture. Future work will expand to a larger patient population with other cancer types, evaluate impact on outcomes, and assess optimal frequency for PRO collection and alert thresholds. [Table: see text]

Misery Loves Company: Presenting Symptom Clusters to Urgent Care by Patients Receiving Antineoplastic Therapy

PURPOSE

The Centers for Medicare & Medicaid Services (CMS) identifies suboptimal management of treatment toxicities as a care gap and proposes the measurement of hospital performance on the basis of emergency department visits for 10 common symptoms. Current management strategies do not address symptom co-occurrence.

METHODS

We evaluated symptom co-occurrence in three patient cohorts that presented to a cancer hospital urgent care center in 2016. We examined both the CMS-identified symptoms and an expanded clinician-identified set defined as symptoms that could be safely managed in the outpatient setting if identified early and managed proactively. The cohorts included patients who presented with a CMS-defined symptom within 30 days of treatment, patients who presented within 30 days of treatment with a symptom from the expanded set, and patients who presented with a symptom from the expanded set within 30 days of treatment start. Symptom co-occurrence was measured by Jaccard index. A community detection algorithm was used to identify symptom clusters on the basis of a random walk process, and network visualizations were used to illustrate symptom dynamics.

RESULTS

There were 6,429 presentations in the CMS symptom-defined cohort. The network analysis identified two distinct symptom clusters centered around pain and fever. In the expanded symptom cohort, there were 5,731 visits and six symptom clusters centered around fever, emesis/nausea, fatigue, deep vein thrombosis, pain, and ascites. For patients who newly initiated treatment, there were 1,154 visits and four symptom clusters centered around fever, nausea/emesis, fatigue, and deep vein thrombosis.

CONCLUSION

Uncontrolled symptoms are associated with unplanned acute care. Recognition of the complexity of symptom co-occurrence can drive improved management strategies.

The next generation of quality improvement at MSK: Turning chemotherapy process delays into chemo express

e18230

Background: Chemotherapy wait times can dramatically affect patient experience. MSK’s largest outpatient facility has 76 infusion spaces and 250-300 daily visits. A retrospective review of the facility’s infusion area wait times suggested that the lab (where all patients go to get their vitals and blood drawn) was a major bottleneck leading to process delays in infusion. Methods: We conducted a pilot program using a multi-pronged approach. Our goal was to decrease wait time from 40 minutes to an average of 15 minutes. Our initiative was defined as follows: (1) to redefine lab parameters that are relevant for toxicity and to only consider drawing those necessary labs; additionally, we created guidelines for timing of the labs prior to infusion treatment, (2) to introduce a program known as “ChemoExpress” which offers patients the opportunity to get blood work done prior to the day of their infusion appointment. After the labs result, the outpatient RN calls the patient, assesses symptoms and “clears them” for treatment cueing the pharmacy to prepare and “premix” the drug on the day of treatment. Results: 150 patients have enrolled in ChemoExpress. Patient satisfaction was high based on patient satisfaction surveys (n = 20). Average wait time was 9 minutes (76% less) in ChemoExpress participants as compared to an average wait of 39 minutes for those who did not participate in ChemoExpress. Conclusions: Implementing a process that enables patients to have their bloodwork drawn prior to the day of treatment and drugs prepared in advance of their treatment appointment results in greater efficiency in the overall workflow. It also offers the patient a lower wait time and a more efficient and satisfying experience.

Doxorubicin followed by sequential paclitaxel and cyclophosphamide versus concurrent paclitaxel and cyclophosphamide: 5-year results of a phase II randomized trial of adjuvant dose-dense chemotherapy for women with node-positive breast carcinoma

PURPOSE

We conducted a randomized Phase II trial to directly compare toxicity, feasibility, and delivered dose intensities of two adjuvant dose-intensive regimens containing doxorubicin, paclitaxel, and cyclophosphamide for patients with node-positive breast carcinoma.

EXPERIMENTAL DESIGN

Forty-two patients with resected breast carcinoma involving one or more ipsilateral axillary lymph nodes, were randomized to receive two different schedules of adjuvant chemotherapy using 14-day dosing intervals: either (a) three cycles of doxorubicin 80 mg/m(2) as i.v. bolus followed sequentially by three cycles of paclitaxel 200 mg/m(2) as a 24-h infusion and then by three cycles of cyclophosphamide 3.0 g/m(2) as a 1-h infusion (arm A); or (b) the same schedule of doxorubicin followed by three cycles of concurrent cyclophosphamide and paclitaxel at the same doses (arm B). All cycles were supported by granulocyte colony-stimulating factor administration.

RESULTS

Forty-one patients were assessable for toxicity and feasibility; 37 (90%) completed all planned chemotherapy. There was no treatment-related mortality; however, increased toxicity was observed on arm B compared with arm A, manifested by an increase in hospitalization for toxicity, mainly neutropenic fever, and an increased incidence of transfusion of packed RBCs transfusions for anemia. The mean delivered dose intensities for paclitaxel and cyclophosphamide were significantly greater for arm A compared with arm B (P =.01 and P =.05, respectively). There is no long-term, treatment-related toxicity, and no cases of acute myelogenous leukemia or myelodysplastic syndrome have been observed.

CONCLUSIONS

Dose-dense sequential single-agent chemotherapy is more feasible than doxorubicin with subsequent concurrent paclitaxel and cyclophosphamide.

5-year results of dose-intensive sequential adjuvant chemotherapy for women with high-risk node-positive breast cancer: A phase II study

PURPOSE

We conducted a phase II pilot study of dose-intensive adjuvant chemotherapy with doxorubicin followed sequentially by high-dose cyclophosphamide to determine the safety and feasibility of this dose-dense treatment and to estimate the disease-free and overall survival in breast cancer patients with four or more involved axillary lymph nodes.

PATIENTS AND METHODS

Seventy-three patients received adjuvant treatment with four cycles of doxorubicin 75 mg/m(2) as an intravenous bolus every 21 days, followed by three cycles of cyclophosphamide 3,000 mg/m(2) every 14 days with granulocyte colony-stimulating factor support.

RESULTS

Seventy-one patients were assessable, and all but two completed all planned chemotherapy. There was no treatment-related mortality. The most common toxicity was neutropenic fever, which occurred in 39% of patients. Median disease-free survival is 66 months (95% confidence interval, 34 to 98 months), and median overall survival has not yet been reached. At 5 years of follow-up, the disease-free survival is 51.7%, and overall survival is 60.0%. There is no long-term treatment-related toxicity, and no cases of acute myelogenous leukemia or myelodysplastic syndrome have been observed.

CONCLUSION

Our pilot study of doxorubicin followed by cyclophosphamide demonstrates the safety and feasibility of the sequential dose-dense plan. Long-term follow-up, although noncomparative, is promising. However, this regimen is associated with a higher incidence of toxicity (and also higher costs) than the standard dose and schedule of doxorubicin and cyclophosphamide, and therefore it should not be used as conventional therapy in the absence of demonstrated improvement of outcome. Randomized trials testing the dose-dense approach have been completed but not yet reported. Because the sequential plan can decrease overlapping toxicities, it is an appropriate platform for the addition of newer active agents, such as taxanes or monoclonal antibodies.

Ninety-six-hour paclitaxel infusion after progression during short taxane exposure: a phase II pharmacokinetic and pharmacodynamic study in metastatic breast cancer

PURPOSE

A phase II trial of paclitaxel infused over 96 hours in patients with metastatic breast cancer with demonstrated disease progression (PD) during short-infusion taxane treatment was performed to evaluate schedule-dependent activity with prolonged drug exposure. The tolerability of this strategy and its pharmacokinetic profile and pharmacodynamic correlates were also investigated.

PATIENTS AND METHODS

Paclitaxel was administered to 26 patients with metastatic breast cancer at 120 to 140 mg/m2 intravenously over 96 hours. Twenty-three patients had demonstrated PD while receiving prior 3-hour paclitaxel, two during 1-hour docetaxel, and one during infusions of docetaxel and then paclitaxel. Twenty-one patients (81%) had no prior response to the short taxane infusion (primary resistance) and five (19%) had prior partial responses (PRs) of brief duration before PD (secondary resistance). Plasma paclitaxel concentrations were assessed at 24, 48, 72, and 96 hours.

RESULTS

After delivery of 195 cycles, seven of 26 assessable patients (26.9%; 95% confidence interval, 11.6% to 47.8%) had major objective responses, with a median response duration of 6 months (range, 1 to 13). The predominant toxicities were neutropenia (76% grade > or = 3) and stomatitis (15% grade > or = 3). Despite omission of premedications, no significant hypersensitivity reactions occurred. The median steady-state paclitaxel concentration (Css) in 23 assessable patients was 0.047 mumol/L (range, .023 to .176). Patients who experienced grade 4 neutropenia had significantly decreased paclitaxel clearance and higher Css than those with grade 1 to 3 neutropenia (P < .05). Pretreatment elevation of hepatic transaminases was associated with delayed clearance (P < .01) and increased myelo-suppression and mucosal toxicity.

CONCLUSION

Paclitaxel demonstrates activity against metastatic breast cancer when administered over 96 hours to patients with disease that recently had progressed during short taxane exposure. Delayed paclitaxel clearance and consequent increased toxicity occurred in patients with hepatic dysfunction. The activity observed supports preclinical data that suggest variability in efficacy and resistance patterns to paclitaxel based on duration of exposure.