Abstract
Purpose: Lymphoma consists of a heterogeneous group of cancers that range from indolent to aggressive, and differentiating malignant lymphomas from non-cancer diagnoses often constitutes a challenge for healthcare professionals. Essential first steps in optimal care require establishing an accurate diagnosis and determination of stage. We hypothesized that patients with clinical suspicion of lymphoma but without definitive diagnosis would be most efficiently evaluated by a dedicated program to streamline patient intake. At Memorial Sloan Kettering (MSK), we created an advanced practice provider (APP)-led lymphoma diagnostic program (LDP) to expedite entry and subsequent workup for patients and assessed whether the APP-LDP workflow reduced wait times for definitive diagnosis and access to care.
Patients and Methods: We reviewed patients referred to MSK with radiographic imaging or inconclusive pathology that were suggestive of lymphoma from December 1, 2022 to March 31, 2024. Patients via the APP-LDP were matched to patients referred to physicians via the Patient Access Service (PAS) within the same time period based on age and sex. Propensity score matching was done independently among three disease types: aggressive, indolent, and non-cancer. Among the patients with aggressive and indolent lymphomas, a 1:4 nearest neighbor matching (NNM) with a 0.2 caliper cutoff of APP-LDP to PAS patients was attempted. Because of the limited number of non-cancer patients via the traditional PAS, a 1:1 matching was attempted among the non-cancer patients.
Three different time intervals were compared between the APP-LDP vs PAS patients: time from referral date to first visit with an APP or physician at MSK (TRFV), time from referral date to diagnostic biopsy at MSK (TRDB), and time from referral date to first treatment at MSK (TRFT). TRFV, TRDB, and TRFT were estimated using the cumulative incidence method, and Cox proportional hazards regression models were used to compare the hazard of first APP or physician visit, definitive diagnosis, and initiating treatment, respectively. A two-sided P-value of <0.05 was considered statistically significant. Statistical analyses were done using SAS 9.4 (SAS Institute Inc. Cary. NC, USA).
Results: From December 1, 2022 through March 31, 2024, 55 patients were referred to MSK's APP-LDP with suspected lymphoma. A 1:4 propensity score matching via the NNM approach with a 0.2 caliper cutoff was applied to 20 patients with aggressive subtypes and 19 patients with indolent subtypes. A 1:1 matching was applied to 16 patients with non-cancer diagnoses. All 20 APP-LDP patients with aggressive subtypes had 4 matches each, 18 APP-LDP patients with indolent subtypes had 4 matches each, and 13 APP-LDP non-cancer patients had 1 match each. In total, 51 patients via the APP-LDP were matched to 165 patients via the traditional PAS within the specified caliper cutoff.
Compared to the patients via the traditional PAS, patients via the APP-LDP had a shorter TRFV (HR, 2.27; 95% CI, 1.53-3.36; p < 0.001), with a median TRFV of 10 days (95% CI, 7 – 12) via the APP-LDP vs 19 days (95%, 15 – 20) via the traditional PAS. Patients via the APP-LDP demonstrated a shorter TRDB (HR, 1.83; 95% CI, 1.27 – 2.62; p = 0.001) compared to patients via the traditional PAS: median TRDB was 20 days (95% CI, 15 – 25) with the APP-LDP vs 27 days (95% CI, 21 – 30) with the traditional PAS. Patients via the APP-LDP also demonstrated a similar TRFT association compared to the traditional PAS patients (HR, 1.40; 95% CI, 0.85 – 2.30; p = 0.187), but this association was not statistically significant: median TRFT was 56 days (95% CI, 34 – 165) with the APP-LDP vs 87 days (95% CI, 67 – not reached) with the traditional PAS.
Conclusion: To our knowledge, this is the first retrospective propensity score matched analysis evaluating the efficacy of an APP-led program dedicated to expediting entry and subsequent workup for patients with suspected lymphoma. The APP-LDP was effective in reducing time to diagnosis and access to care by facilitating appointments with expert clinicians who utilize state-of-the-art diagnostic tools, and by streamlining collaboration between hospital administration, APPs, and physician leaders. Findings from this study support the ongoing efforts to create similar APP-led programs at MSK, the CLL Observation Program and the CML and ALL Survivorship Program, with the aim of improving new visit access.
