Predictors of diagnostic interval and associations with outcome in acute lymphoblastic leukemia

Time to diagnosis among young patients with cancer

BACKGROUND

Sociodemographic and clinical factors associated with diagnostic delays in pediatric, adolescent, and young adult cancers are poorly understood.

METHODS

Using the Optum Labs Data Warehouse's de-identified claims data for commercial health plan enrollees, we identified children (0-14 years) and adolescents/young adults (AYAs) (15-39 years) diagnosed with one of 10 common cancers from 2001 to 2017, who were continuously enrolled for 6 months preceding diagnosis. Time to diagnosis was calculated as days between first medical encounter with possible cancer symptoms and cancer diagnosis date. Median times from first symptom to diagnosis were compared using Wilcoxon rank sum test. Multivariable unconditional logistic regression identified sociodemographic factors associated with longer time (>3 months) to cancer diagnosis (from symptom onset).

RESULTS

Of 47,296 patients, 87% presented prior to diagnosis with symptoms. Patients with central nervous system (CNS) tumors were most likely to present with symptoms (93%), whereas patients with cervical cancer were least likely (70%). Symptoms varied by malignancy. Of patients with symptoms, thyroid (105 days [range: 50-154]) and cervical (104 days [range: 41-151]) cancer had the longest median time to diagnosis. Females and patients at either end of the age spectrum were more likely to experience diagnosis delays of more than 3 months.

CONCLUSION

In a commercially insured population, time to diagnosis varies by cancer type, age, and sex. Further work is needed to understand the patient, provider, and health system-level factors contributing to time from symptom onset to diagnosis, specifically in the very young children and the young adult patient population going forward.

Delayed diagnostic interval and survival outcomes in pediatric leukemia: A single-center, retrospective study

OBJECTIVE

This study primarily focused on the diagnostic interval (DI), defined as the duration from the onset of leukemic symptoms to diagnosis. We investigated whether a prolonged DI is associated with the outcomes of pediatric leukemia.

METHODS

We retrospectively collected data of children with newly diagnosed pediatric leukemia at Okayama University Hospital from January 2007 to December 2022. Survival analyses were conducted using Kaplan-Meier methods, and an unadjusted analysis to compare differences in survival was performed using the log-rank test.

RESULTS

In total, 103 children with leukemia were included in the analysis. The median DI was 20 days (interquartile range, 9.5-33.5 days). A prolonged DI (≥30 days) demonstrated no association with either 5-year event-free survival (70.1% for <30 days and 68.3% for ≥30 days, p = .99, log-rank test) or overall survival (84.7% for <30 days and 89.4% for ≥30 days, p = .85, log-rank test).

CONCLUSIONS

A prolonged DI was not associated with the survival of children with leukemia. If a precise classification of leukemia biology is provided for pediatric patients, a prolonged DI may have little impact on the prognosis of these patients.

Are delays in diagnosis and treatment of acute leukemia in a middle-income country associated with poor outcomes? A retrospective cohort study

INTRODUCTION

Acute leukemias (ALs) are aggressive diseases that lead to death without medical attention. We evaluated the association between delays in diagnosis and poor outcomes in AL by evaluating the symptom onset to treatment intervals in adults with newly diagnosed AL and their effect on an early death (ED).

METHODS

We assessed adults diagnosed with AL between 2015 and 2020 and evaluated baseline characteristics, the patient interval (PI), diagnostic interval (DI), treatment interval (TI) and the total time interval (TTI) to determine ED-associated factors.

MAIN RESULTS

We assessed 102 patients with acute lymphoblastic leukemia (ALL), 57 with acute myeloblastic leukemia (AML) and 29 with acute promyelocytic leukemia (APL). Median interval days were PI 14, DI 10, TI 4 and TTI 31.5. The TI and TTI intervals were lower in APL than in ALL and AML; TI 1 vs. 4 and 3 (p = 0.001) and TTI 21 vs. 31 and 35 (p = 0.016). The 30-day and 60-day EDs were 13.8% and 20.7%, mainly infections. ECOG > 2 (OR = 15.0) and PI < 7 days (OR = 4.06) were associated with 30-day ED; AML (OR = 2.69), high-risk (OR = 3.34), albumin < 3.5 g/dl (OR = 5) and platelets < 20 × 10³/uL (OR = 2.71) with a 60-day ED.

CONCLUSION

None of the interval-delays were associated with an ED. Intervals seemed to be longer in patients without an ED, except for the TI, probably because of "the waiting time paradox." Aggressive manifestations of disease may lead to shorter diagnostic intervals, but increased mortality.

Factors that contribute to disparities in time to acute leukemia diagnosis in young people: an in depth qualitative interview study

BACKGROUND

Racial and ethnic disparities in outcomes for Black and Hispanic children with acute leukemia have been well documented, however little is known about the determinants of diagnostic delays in pediatric leukemia in the United States. The primary objective of this study is to identify factors contributing to delays preceding a pediatric leukemia diagnosis.

METHODS

This qualitative study utilized in-depth semi-structured interviews. Parents and/or patients within two years of receiving a new acute leukemia diagnosis were asked to reflect upon their family's experiences preceding the patient's diagnosis. Subjects were purposively sampled for maximum variation in race, ethnicity, income, and language. Interviews were analyzed using inductive theory-building and the constant comparative method to understand the process of diagnosis. Chart review was conducted to complement qualitative data.

RESULTS

Thirty-two interviews were conducted with a diverse population of English and Spanish speaking participants from two tertiary care pediatric cancer centers. Parents reported feeling frustrated when their intuition conflicted with providers' management decisions. Many felt laboratory testing was not performed soon enough. Additional contributors to delays included misattribution of vague symptoms to more common diagnoses, difficulties in obtaining appointments, and financial disincentives to seek urgent or emergent care. Reports of difficulty obtaining timely appointments and financial concerns were disproportionately raised among low-income Black and Hispanic participants. Comparatively, parents with prior healthcare experiences felt better able to navigate the system and advocate for additional testing at symptom onset.

CONCLUSIONS

While there are disease-related factors contributing to delays in diagnosis, it is important to recognize there are multiple non-disease-related factors that also contribute to delays. Evidence-based approaches to reduce outcome disparities in pediatric cancer likely need to start in the primary care setting where timeliness of diagnosis can be addressed.

Distance to the pediatric oncology center does not affect survival in children with acute lymphoblastic leukemia: a report from CYP-C

Remoteness is associated with worse survival in adults with cancer. We aimed to determine whether remoteness is associated with cancer outcomes in pediatric acute lymphoblastic leukemia (ALL). Canadian children with ALL entered in the CYP-C registry were included. The predictive impact of remoteness on overall survival (OS), relapse, and treatment-related complications (infections, thrombosis, bleeding, and osteonecrosis) was estimated using multivariate regression models. We included 1383 children, of whom 277 (20.0%) lived remotely (>200 km from the pediatric oncology center). The median latency to see a pediatric oncologist was longer in children living remotely. The 5-year OS (95% CI) was similar for both groups (remote: 95.2% [93.7-96.3%] vs close: 94.1% [90.5-95.2%]). No difference was found in the relapse rate between both groups and in treatment-related complications. Remoteness did not affect survival in pediatric ALL. Further research is needed to determine which models of healthcare organization optimize cancer outcomes and patients' satisfaction.

Paediatricians provide higher quality care to children and adolescents in primary care: A systematic review

AIM

The number of primary care paediatricians is decreasing in Europe without a justifiable reason. We aimed to compare the clinical practice of paediatricians and family doctors attending children and adolescents in primary care.

METHODS

MEDLINE, Embase, CENTRAL, TRIP and Google Scholar were searched from December 2008 to February 2018. No language or study design restrictions were applied. Three reviewers assessed eligibility of the studies. Seven pairs of reviewers performed the data extraction and assessed the methodological quality independently. Discrepancies were resolved by consensus.

RESULTS

Fifty-four, out of 1150 studies preselected, were included. We found that paediatricians show more appropriate pharmacology prescription patterns for the illness being treated; they achieve higher vaccination rates and have better knowledge of vaccines and fewer doubts about vaccine safety; their knowledge and implementation of different screening tests are better; they prescribe psychoactive drugs more cautiously and more in line with current practice guidelines; their evaluation and treatment of obesity and lipid disorders follow criteria more consistently with current clinical practice guidelines; and they perform fewer diagnostic test, show a more suitable use of the test and request fewer referrals to specialists.

CONCLUSION

According to published data, in developed countries, paediatricians provide higher quality care to children than family doctors.

Which indicators of early cancer diagnosis from population-based data sources are associated with short-term mortality and survival?

BACKGROUND

A key component of recent English cancer policy is the monitoring of trends in early diagnosis of cancer. Early diagnosis can be defined by the disease stage at diagnosis or by other indicators derived from electronic health records. We evaluate the association between different early diagnosis indicators and survival, and discuss the implementation of the indicators in surveillance of early diagnosis.

METHODS

We searched the PubMed database and grey literature to identify early diagnosis indicators and evaluate their association with survival. We analysed cancer registrations for 355,502 cancer patients diagnosed in England during the period 2009-2013, and quantified the association between each early diagnosis indicator and 30-day mortality and five-year net survival.

RESULTS

Each incremental difference in stage (I-IV) predicts lower 5-year survival, so prognostic information is lost in comparisons which use binary stage indicators. Patients without a recorded stage have high risk of death shortly following diagnosis and lower 5-year survival. Emergency presentation is independently associated with lower five-year survival. Shorter intervals between first symptoms and diagnosis are not consistently associated with improved survival, potentially due to confounding from tumour characteristics.

INTERPRETATION

Contrary to current practice, we recommend that all the stage information should be used in surveillance. Patients missing stage should also be included to minimise bias. Combined data on stage and emergency presentation could be used to create summary prognostic measures. More work is needed to create statistics based on the diagnostic interval that will be useful for surveillance.

Predictors of Specialized Pediatric Palliative Care Involvement and Impact on Patterns of End-of-Life Care in Children With Cancer

Purpose

The impact of specialized pediatric palliative care (SPPC) teams on patterns of end-of-life care is unknown. We sought to determine (1) which children with cancer access SPPC and (2) the impact of accessing SPPC on the risk of experiencing high-intensity end-of-life care (intensive care unit admission, mechanical ventilation, or in-hospital death).

Methods

Using a provincial childhood cancer registry, we assembled a retrospective cohort of Ontario children with cancer who died between 2000 and 2012 and received care through pediatric institutions with an SPPC team. Patients were linked to population-based administrative data capturing inpatient, outpatient, and emergency visits. Children were classified as having SPPC, general palliative care, or no palliative care on the basis of SPPC clinical databases, physician billing codes, or inpatient diagnosis codes.

Results

Of the 572 children, 166 (29%) received care from an SPPC team for at least 30 days before death, and 100 (17.5%) received general palliative care. SPPC involvement was significantly less likely for children with hematologic cancers (OR, 0.3; 95% CI, 0.3 to 0.4), living in the lowest income areas (OR, 0.4; 95% CI, 0.2 to 0.8), and living further from the treatment center (OR, 0.5; 95% CI, 0.4 to 0.5). SPPC was associated with a five-fold decrease in odds of intensive care unit admission (OR, 0.2; 95% CI, 0.1 to 0.4), whereas general palliative care had no impact. Similar associations were seen with all secondary indicators.

Conclusion

When available, SPPC, but not general palliative care, is associated with lower intensity care at the end of life for children with cancer. However, access remains uneven. These results provide the strongest evidence to date supporting the creation of SPPC teams.

Patterns of Diagnosis and Misdiagnosis in Pediatric Cancer and Relationship to Survival

BACKGROUND

Pediatric cancer is rare and its symptoms are often ambiguous. The aims of this study were to investigate the time needed to make a diagnosis, assess the frequency of misdiagnosis, and to determine whether these factors affected survival.

METHODS

A review of records of 364 pediatric patients diagnosed with cancer at the University of Rochester Golisano Children's Hospital between 2004 and 2012 was conducted. Data were extracted on patient and health care system-related factors and clinical outcomes.

RESULTS

The median time from symptom onset to diagnosis was shortest for leukemia (18.5 d) and longest for bone tumors (86.5 d). Tumor type was the only factor associated with time to diagnosis. In 52% of cases an incorrect nononcological diagnosis was initially made. Soft tissue sarcomas and brain tumors were misdiagnosed most often. Neither prolonged time to diagnosis nor initial misdiagnosis was associated with reduced survival. Tumor type and presence of metastatic disease at diagnosis were significantly associated with survival.

CONCLUSIONS

There is significant variation in the time from symptom onset to diagnosis of pediatric cancers, and incorrect initial diagnostic impressions are common. Despite this there is no impact of prolonged time to diagnosis on survival.

Predictors of and Trends in High-Intensity End-of-Life Care Among Children With Cancer: A Population-Based Study Using Health Services Data

Purpose

Children with cancer often receive high-intensity (HI) medical care at the end-of-life (EOL). Previous studies have been limited to single centers or lacked detailed clinical data. We determined predictors of and trends in HI-EOL care by linking population-based clinical and health-services databases.

Methods

A retrospective decedent cohort of patients with childhood cancer who died between 2000 and 2012 in Ontario, Canada, was assembled using a provincial cancer registry and linked to population-based health-care data. Based on previous studies, the primary composite measure of HI-EOL care comprised any of the following: intravenous chemotherapy < 14 days from death; more than one emergency department visit; and more than one hospitalization or intensive care unit admission < 30 days from death. Secondary measures included those same individual measures and measures of the most invasive (MI) EOL care (eg, mechanical ventilation < 14 days from death). We determined predictors of outcomes with appropriate regression models. Sensitivity analysis was restricted to cases of cancer-related mortality, excluding treatment-related mortality (TRM) cases.

Results

The study included 815 patients; of these, 331 (40.6%) experienced HI-EOL care. Those with hematologic malignancies were at highest risk (odds ratio, 2.5; 95% CI, 1.8 to 3.6; P < .001). Patients with hematologic cancers and those who died after 2004 were more likely to experience the MI-EOL care (eg, intensive care unit, mechanical ventilation, odds ratios from 2.0 to 5.1). Excluding cases of TRM did not substantively change the results.

Conclusion

Ontario children with cancer continue to experience HI-EOL care. Patients with hematologic malignancies are at highest risk even when excluding TRM. Of concern, rates of the MI-EOL care have increased over time despite increased palliative care access. Linking health services and clinical data allows monitoring of population trends in EOL care and identifies high-risk populations for future interventions.

The expanding role of primary care in cancer control

The nature of cancer control is changing, with an increasing emphasis, fuelled by public and political demand, on prevention, early diagnosis, and patient experience during and after treatment. At the same time, primary care is increasingly promoted, by governments and health funders worldwide, as the preferred setting for most health care for reasons of increasing need, to stabilise health-care costs, and to accommodate patient preference for care close to home. It is timely, then, to consider how this expanding role for primary care can work for cancer control, which has long been dominated by highly technical interventions centred on treatment, and in which the contribution of primary care has been largely perceived as marginal. In this Commission, expert opinion from primary care and public health professionals with academic and clinical cancer expertise—from epidemiologists, psychologists, policy makers, and cancer specialists—has contributed to a detailed consideration of the evidence for cancer control provided in primary care and community care settings. Ranging from primary prevention to end-of-life care, the scope for new models of care is explored, and the actions needed to effect change are outlined. The strengths of primary care—its continuous, coordinated, and comprehensive care for individuals and families—are particularly evident in prevention and diagnosis, in shared follow-up and survivorship care, and in end-of-life care. A strong theme of integration of care runs throughout, and its elements (clinical, vertical, and functional) and the tools needed for integrated working are described in detail. All of this change, as it evolves, will need to be underpinned by new research and by continuing and shared multiprofessional development.