General practitioner involvement in follow-up of childhood cancer survivors: a systematic review

BACKGROUND An increasing number of childhood cancer survivors need long-term follow-up care. Different models address this problem, including that of follow-up by general practitioners (GP). We describe models that involve GPs in follow-up for childhood cancer survivors, their advantages and disadvantages, clinics that employ these models, and the elements essential to high-quality, GP-led follow-up care. PROCEDURE We searched four databases (PubMed [including Medline], Embase, Cochrane, and CINAHL) without language restrictions. RESULTS We found 26 publications, which explicitly mentioned GP-led follow-up. Two models were commonly described: GP-only, and shared care between GP and pediatric oncology or late effects clinic. The shared care model appears to have advantages over GP-only follow-up. We found four clinics using models of GP-led follow-up, described in five papers. We identified well-organized transition, treatment summary, survivorship care plan, education of GPs and guidelines as necessary components of successful follow-up. CONCLUSION Scarcity of literature necessitated a review rather than a meta-analysis. More research on the outcomes of GP-led care is necessary to confirm the model for follow-up of childhood cancer survivors in the long term. However, with the necessary elements in place, the model of GP-led follow-up, and shared care in particular, holds promise

Intra-Rater and Inter-Rater Reliability of a Medical Record Abstraction Study on Transition of Care after Childhood Cancer.

BACKGROUND The abstraction of data from medical records is a widespread practice in epidemiological research. However, studies using this means of data collection rarely report reliability. Within the Transition after Childhood Cancer Study (TaCC) which is based on a medical record abstraction, we conducted a second independent abstraction of data with the aim to assess a) intra-rater reliability of one rater at two time points; b) the possible learning effects between these two time points compared to a gold-standard; and c) inter-rater reliability. METHOD Within the TaCC study we conducted a systematic medical record abstraction in the 9 Swiss clinics with pediatric oncology wards. In a second phase we selected a subsample of medical records in 3 clinics to conduct a second independent abstraction. We then assessed intra-rater reliability at two time points, the learning effect over time (comparing each rater at two time-points with a gold-standard) and the inter-rater reliability of a selected number of variables. We calculated percentage agreement and Cohen's kappa. FINDINGS For the assessment of the intra-rater reliability we included 154 records (80 for rater 1; 74 for rater 2). For the inter-rater reliability we could include 70 records. Intra-rater reliability was substantial to excellent (Cohen's kappa 0-6-0.8) with an observed percentage agreement of 75%-95%. In all variables learning effects were observed. Inter-rater reliability was substantial to excellent (Cohen's kappa 0.70-0.83) with high agreement ranging from 86% to 100%. CONCLUSIONS Our study showed that data abstracted from medical records are reliable. Investigating intra-rater and inter-rater reliability can give confidence to draw conclusions from the abstracted data and increase data quality by minimizing systematic errors

Cancer's positive flip side: posttraumatic growth after childhood cancer.

BACKGROUND Surviving childhood cancer may result in positive psychological changes called posttraumatic growth (PTG). Knowing about the possibility of positive changes may facilitate survivors' reintegration in daily life. We aimed to (1) describe PTG in Swiss childhood cancer survivors including the most and the least common PTG phenomena on the subscale and item levels and (2) determine factors associated with PTG. METHOD Within the Swiss Childhood Cancer Survivor Study (SCCSS), we sent two questionnaires to childhood cancer survivors registered in the Swiss Childhood Cancer Registry (SCCR). Eligible survivors were diagnosed after 1990 at age ≤16 years, survived ≥5 years, and were aged ≥18 years at the time the second questionnaire was sent. We included the Posttraumatic Growth Inventory (PTGI) to assess five areas of PTG. We investigated the association of PTG with socio-demographic characteristics, self-reported late effects, and psychological distress, which were assessed in the SCCSS and clinical variables extracted from the SCCR. We used descriptive statistics to describe PTG and linear regressions to investigate factors associated with PTG. RESULTS We assessed PTG in 309 childhood cancer survivors. Most individuals reported to have experienced some PTG. The most endorsed change occurred in "relation with others," the least in "spiritual change." PTG was significantly higher in survivors with older age at diagnosis (p = 0.001) and those with a longer duration of treatment (p = 0.042), while it was lower in male survivors (p = 0.003). CONCLUSIONS Supporting experiences of PTG during follow-up may help survivors successfully return to daily life

Kappa values and their interpretation for intra-rater and inter-rater reliability.

<p>Fig 2 shows the values of kappa for intra-rater (dark blue) and for inter-rater (light blue) reliability with their confidence intervals T for each variable under investigation.</p

Inter-rater reliability.

<p>Abbreviations: CI, Confidence Interval; kappa, Cohen’s kappa; n.a., not applicable; PABAK, Prevalence and Bias Adjusted Kappa.</p><p>Inter-rater reliability.</p

Variables assessed in the re-abstraction.

<p>The categorical variables represent a more challenging collection than date variables because the corresponding information had to be found in free text and often necessitated an interpretation.</p><p>Variables assessed in the re-abstraction.</p

Kappa values and Prevalence-adjusted Bias-adjusted kappa values for intra-rater (a) and inter-rater reliability (b).

<p>Fig 3a and 3b show the values of kappa compared to the the values obtained by calculating the Prevalence-adjusted Bias-adjusted kappa for intra-rater reliability (a) and inter-rater reliability (b).</p

Intra-rater reliability.

<p>Abbreviations: CI, Confidence Interval; kappa, Cohen’s kappa; n.a., not applicable; PABAK, Prevalence and Bias Adjusted Kappa.</p><p>Intra-rater reliability.</p

Flow chart of sample selection for reliability assessment.

<p>Fig 1 shows the flow chart of our study population starting from those eligible to those included in the analysis.</p