Challenges in Treating Cancer Patients With Unstable Psychiatric Disorder
Bibliographic record
Abstract
In this review, we first present a case of chronic myeloid leukemia with acute psychosis, and then we will discuss the incidence of cancer in patients with psychotic disorders, the manifestations of new-onset psychosis, and the prevalence of preexisting psychosis in cancer patients, coupled with their impact on the treatment, diagnosis, and prognosis of cancer. This was a case that presented with acute psychosis and was found to have an elevated white blood cell count upon admission to an inpatient psychiatric unit. He was diagnosed with chronic myeloid leukemia and successfully managed with imatinib/dasatinib therapy. Psychiatrically, he was stabilized on two long-acting injectable medications to help maintain adherence. We were able to eliminate his active psychotic symptoms and return him to normal functioning in affect and thinking, achieving sustained compliance with treatment. We identified multiple inconsistencies in screening for cancer of all types in these patients, masking of signs and symptoms that would typically clue physicians to the presence of cancers, underreporting of symptoms, and disparate access to healthcare resources in patients with mental disorders when compared to the general population. Treatment of cancer in these patients as compared to the general population has also been shown to be incongruent, which will be elaborated upon. Psychiatric interventions, as well as supportive measures, for treating patients who are facing challenges during active cancer treatment will be discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".