The Serious Illness Conversation Guide Is Meaningful to Patients with Hematologic Malignancies and Impacts Death in Acute Care
Bibliographic record
Abstract
Patients with hematologic malignancies have a high likelihood of dying with acute care (Korsos, 2023). Death in an acute care setting prevents patients and their families from preparing for end of life (EOL) and diminishes quality of life (QoL). We hypothesize that a timely, robust discussion aligning patients' perspectives and goals with their treating team will facilitate optimal care at EOL. We are thus conducting a prospective, mixed-methods study looking at the benefit of a guided discussion tool, the Serious Illness Conversation Guide (SICG) (Bernacki, 2019), in patients with hematologic malignancies nearing EOL, which has been studied in general oncology but not specifically in hematologic malignancies. We evaluated the SICG using patient questionnaires, semi-structured interviews and by assessing EOL outcomes among patients who had the SIC. Eligible participants had an estimated survival of less than one year and were fluent in English or French. Study members (4 hematologists and 1 nurse practitioner) were trained on the SICG by a palliative care physician using the official training program (Bernacki, 2015). Patients were approached for study consent, administered the SIC in the outpatient or inpatient setting, and asked to complete the SICG impact survey (Paladino, 2020). Twelve patients participated in semi-structured interviews 2-6 weeks later. Interviews were recorded and transcribed verbatim. Inductive thematic analysis was done by two hematologists and one psychologist. Each independently coded a transcript prior to group discussion and themes were assigned. Analysis continued until themes were saturated. Relevant clinical data was collected prospectively to measure the rate of death in acute care. We report results at pre-specified one-year interim analysis among 15 of 34 enrolled patients for the impact survey and EOL outcomes, and final results of SICG feedback from 12 patient interviews. Of the 15 patients, 10 were male (67%), 5 female (33%); mean age 68 years (42-84); 9 were Caucasian (73%), 1 was Black (8.3%) and 2 North African (17%); 7 had acute leukemia (47%), 2 MDS (13%), 3 lymphoma/CLL (20%) and 3 myeloma (20%). Among the 15 patients, 11 had died: 3 with medical assistance in dying (MAID), 5 with palliative care at home or in hospital, 1 during resuscitation efforts and 2 in intensive care. Thus, 8 of 11 (72%) patients died outside of an acute care setting with palliative goals. Of the 11 patients who died, 4 had a change in goals of care shortly after the SIC. The feedback from the SICG impact survey was positive. All patients found the SIC to be very much or extremely worthwhile. Sense of control and peacefulness improved in most cases. Hopefulness and hopefulness for quality of life improved in most cases with two participants experiencing a slight decrease. Closeness to their physician increased a little or a lot in nearly all cases. Anxiety did not change in most cases or even decreased a little. Patients felt they got the right amount or more information than expected. Finally, patients felt the conversation was held at the right time or could even have been earlier. Analysis of patient interviews was positive with no improvements suggested. Patients felt the SIC brought on emotions which were not harmful, facilitated conversations around difficult topics that were on their mind, and helped them accept their illness and prognosis. The SIC allowed them to plan for possible EOL by providing a realistic timeline. The SIC also strengthened connections. It deepened bonds with family when included. It allowed patients to feel known as a person by their doctor, not just as a patient with cancer. It even “reset” the relationship with the care team in those who felt previously abandoned. To our knowledge, ours is the first study to examine the value of the SICG in patients with hematologic malignancies. These interim findings suggest a decrease in death in acute care in patients who had a SIC. Whereas 60% of patients died in acute care in hour historical cohort (Korsos, 2023) only 3 patients (28%) did so in this study. Interim findings are striking for the positive emotional effects described by patients, given providers hesitate to discuss serious illness topics out of fear of taking away hope (Odejide, 2016). The SICG had a humanizing effect that empowered patients. The semi-structured interviews with patients provide a nuanced view, which begins to fill a gap in the literature for these patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".